mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-10-22 16:23:08 +00:00
Clean up backup files
This commit is contained in:
Ashwin Bharambe
parent
b1659369e8
commit
14c23dd5de
10 changed files with 0 additions and 1629 deletions
|
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@ -1,121 +0,0 @@
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|||
version: 2
|
||||
image_name: dell
|
||||
apis:
|
||||
- agents
|
||||
- datasetio
|
||||
- eval
|
||||
- inference
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
|
||||
providers:
|
||||
inference:
|
||||
- provider_id: tgi0
|
||||
provider_type: remote::tgi
|
||||
config:
|
||||
url: ${env.DEH_URL}
|
||||
- provider_id: sentence-transformers
|
||||
provider_type: inline::sentence-transformers
|
||||
vector_io:
|
||||
- provider_id: chromadb
|
||||
provider_type: remote::chromadb
|
||||
config:
|
||||
url: ${env.CHROMADB_URL:=}
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell/}/chroma_remote_registry.db
|
||||
safety:
|
||||
- provider_id: llama-guard
|
||||
provider_type: inline::llama-guard
|
||||
config:
|
||||
excluded_categories: []
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
eval:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/meta_reference_eval.db
|
||||
datasetio:
|
||||
- provider_id: huggingface
|
||||
provider_type: remote::huggingface
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/huggingface_datasetio.db
|
||||
- provider_id: localfs
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/localfs_datasetio.db
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
- provider_id: llm-as-judge
|
||||
provider_type: inline::llm-as-judge
|
||||
- provider_id: braintrust
|
||||
provider_type: inline::braintrust
|
||||
config:
|
||||
openai_api_key: ${env.OPENAI_API_KEY:=}
|
||||
tool_runtime:
|
||||
- provider_id: brave-search
|
||||
provider_type: remote::brave-search
|
||||
config:
|
||||
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: tavily-search
|
||||
provider_type: remote::tavily-search
|
||||
config:
|
||||
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/dell}/inference_store.db
|
||||
models:
|
||||
- metadata: {}
|
||||
model_id: ${env.INFERENCE_MODEL}
|
||||
provider_id: tgi0
|
||||
model_type: llm
|
||||
- metadata:
|
||||
embedding_dimension: 384
|
||||
model_id: all-MiniLM-L6-v2
|
||||
provider_id: sentence-transformers
|
||||
model_type: embedding
|
||||
shields: []
|
||||
vector_dbs: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: brave-search
|
||||
- toolgroup_id: builtin::rag
|
||||
provider_id: rag-runtime
|
||||
server:
|
||||
port: 8321
|
||||
|
|
@ -1,128 +0,0 @@
|
|||
version: 2
|
||||
image_name: meta-reference-gpu
|
||||
apis:
|
||||
- agents
|
||||
- datasetio
|
||||
- eval
|
||||
- inference
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
|
||||
providers:
|
||||
inference:
|
||||
- provider_id: meta-reference-inference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
model: ${env.INFERENCE_MODEL}
|
||||
checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:=null}
|
||||
quantization:
|
||||
type: ${env.QUANTIZATION_TYPE:=bf16}
|
||||
model_parallel_size: ${env.MODEL_PARALLEL_SIZE:=0}
|
||||
max_batch_size: ${env.MAX_BATCH_SIZE:=1}
|
||||
max_seq_len: ${env.MAX_SEQ_LEN:=4096}
|
||||
- provider_id: sentence-transformers
|
||||
provider_type: inline::sentence-transformers
|
||||
vector_io:
|
||||
- provider_id: faiss
|
||||
provider_type: inline::faiss
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/faiss_store.db
|
||||
safety:
|
||||
- provider_id: llama-guard
|
||||
provider_type: inline::llama-guard
|
||||
config:
|
||||
excluded_categories: []
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
eval:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/meta_reference_eval.db
|
||||
datasetio:
|
||||
- provider_id: huggingface
|
||||
provider_type: remote::huggingface
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/huggingface_datasetio.db
|
||||
- provider_id: localfs
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/localfs_datasetio.db
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
- provider_id: llm-as-judge
|
||||
provider_type: inline::llm-as-judge
|
||||
- provider_id: braintrust
|
||||
provider_type: inline::braintrust
|
||||
config:
|
||||
openai_api_key: ${env.OPENAI_API_KEY:=}
|
||||
tool_runtime:
|
||||
- provider_id: brave-search
|
||||
provider_type: remote::brave-search
|
||||
config:
|
||||
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: tavily-search
|
||||
provider_type: remote::tavily-search
|
||||
config:
|
||||
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
- provider_id: model-context-protocol
|
||||
provider_type: remote::model-context-protocol
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/meta-reference-gpu}/inference_store.db
|
||||
models:
|
||||
- metadata: {}
|
||||
model_id: ${env.INFERENCE_MODEL}
|
||||
provider_id: meta-reference-inference
|
||||
model_type: llm
|
||||
- metadata:
|
||||
embedding_dimension: 384
|
||||
model_id: all-MiniLM-L6-v2
|
||||
provider_id: sentence-transformers
|
||||
model_type: embedding
|
||||
shields: []
|
||||
vector_dbs: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
- toolgroup_id: builtin::rag
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||||
provider_id: rag-runtime
|
||||
server:
|
||||
port: 8321
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||||
|
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@ -1,105 +0,0 @@
|
|||
version: 2
|
||||
image_name: nvidia
|
||||
apis:
|
||||
- agents
|
||||
- datasetio
|
||||
- eval
|
||||
- files
|
||||
- inference
|
||||
- post_training
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
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||||
providers:
|
||||
inference:
|
||||
- provider_id: nvidia
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||||
provider_type: remote::nvidia
|
||||
config:
|
||||
url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}
|
||||
api_key: ${env.NVIDIA_API_KEY:=}
|
||||
append_api_version: ${env.NVIDIA_APPEND_API_VERSION:=True}
|
||||
vector_io:
|
||||
- provider_id: faiss
|
||||
provider_type: inline::faiss
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/faiss_store.db
|
||||
safety:
|
||||
- provider_id: nvidia
|
||||
provider_type: remote::nvidia
|
||||
config:
|
||||
guardrails_service_url: ${env.GUARDRAILS_SERVICE_URL:=http://localhost:7331}
|
||||
config_id: ${env.NVIDIA_GUARDRAILS_CONFIG_ID:=self-check}
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
eval:
|
||||
- provider_id: nvidia
|
||||
provider_type: remote::nvidia
|
||||
config:
|
||||
evaluator_url: ${env.NVIDIA_EVALUATOR_URL:=http://localhost:7331}
|
||||
post_training:
|
||||
- provider_id: nvidia
|
||||
provider_type: remote::nvidia
|
||||
config:
|
||||
api_key: ${env.NVIDIA_API_KEY:=}
|
||||
dataset_namespace: ${env.NVIDIA_DATASET_NAMESPACE:=default}
|
||||
project_id: ${env.NVIDIA_PROJECT_ID:=test-project}
|
||||
customizer_url: ${env.NVIDIA_CUSTOMIZER_URL:=http://nemo.test}
|
||||
datasetio:
|
||||
- provider_id: nvidia
|
||||
provider_type: remote::nvidia
|
||||
config:
|
||||
api_key: ${env.NVIDIA_API_KEY:=}
|
||||
dataset_namespace: ${env.NVIDIA_DATASET_NAMESPACE:=default}
|
||||
project_id: ${env.NVIDIA_PROJECT_ID:=test-project}
|
||||
datasets_url: ${env.NVIDIA_DATASETS_URL:=http://nemo.test}
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
tool_runtime:
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
files:
|
||||
- provider_id: meta-reference-files
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/nvidia/files}
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/files_metadata.db
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/nvidia}/inference_store.db
|
||||
models: []
|
||||
shields: []
|
||||
vector_dbs: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::rag
|
||||
provider_id: rag-runtime
|
||||
server:
|
||||
port: 8321
|
||||
|
|
@ -1,241 +0,0 @@
|
|||
version: 2
|
||||
image_name: open-benchmark
|
||||
apis:
|
||||
- agents
|
||||
- datasetio
|
||||
- eval
|
||||
- inference
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
|
||||
providers:
|
||||
inference:
|
||||
- provider_id: openai
|
||||
provider_type: remote::openai
|
||||
config:
|
||||
api_key: ${env.OPENAI_API_KEY:=}
|
||||
base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
|
||||
- provider_id: anthropic
|
||||
provider_type: remote::anthropic
|
||||
config:
|
||||
api_key: ${env.ANTHROPIC_API_KEY:=}
|
||||
- provider_id: gemini
|
||||
provider_type: remote::gemini
|
||||
config:
|
||||
api_key: ${env.GEMINI_API_KEY:=}
|
||||
- provider_id: groq
|
||||
provider_type: remote::groq
|
||||
config:
|
||||
url: https://api.groq.com
|
||||
api_key: ${env.GROQ_API_KEY:=}
|
||||
- provider_id: together
|
||||
provider_type: remote::together
|
||||
config:
|
||||
url: https://api.together.xyz/v1
|
||||
api_key: ${env.TOGETHER_API_KEY:=}
|
||||
vector_io:
|
||||
- provider_id: sqlite-vec
|
||||
provider_type: inline::sqlite-vec
|
||||
config:
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/sqlite_vec.db
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/sqlite_vec_registry.db
|
||||
- provider_id: ${env.ENABLE_CHROMADB:+chromadb}
|
||||
provider_type: remote::chromadb
|
||||
config:
|
||||
url: ${env.CHROMADB_URL:=}
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/chroma_remote_registry.db
|
||||
- provider_id: ${env.ENABLE_PGVECTOR:+pgvector}
|
||||
provider_type: remote::pgvector
|
||||
config:
|
||||
host: ${env.PGVECTOR_HOST:=localhost}
|
||||
port: ${env.PGVECTOR_PORT:=5432}
|
||||
db: ${env.PGVECTOR_DB:=}
|
||||
user: ${env.PGVECTOR_USER:=}
|
||||
password: ${env.PGVECTOR_PASSWORD:=}
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/pgvector_registry.db
|
||||
safety:
|
||||
- provider_id: llama-guard
|
||||
provider_type: inline::llama-guard
|
||||
config:
|
||||
excluded_categories: []
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
eval:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/meta_reference_eval.db
|
||||
datasetio:
|
||||
- provider_id: huggingface
|
||||
provider_type: remote::huggingface
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/huggingface_datasetio.db
|
||||
- provider_id: localfs
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/localfs_datasetio.db
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
- provider_id: llm-as-judge
|
||||
provider_type: inline::llm-as-judge
|
||||
- provider_id: braintrust
|
||||
provider_type: inline::braintrust
|
||||
config:
|
||||
openai_api_key: ${env.OPENAI_API_KEY:=}
|
||||
tool_runtime:
|
||||
- provider_id: brave-search
|
||||
provider_type: remote::brave-search
|
||||
config:
|
||||
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: tavily-search
|
||||
provider_type: remote::tavily-search
|
||||
config:
|
||||
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
- provider_id: model-context-protocol
|
||||
provider_type: remote::model-context-protocol
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/inference_store.db
|
||||
models:
|
||||
- metadata: {}
|
||||
model_id: gpt-4o
|
||||
provider_id: openai
|
||||
provider_model_id: gpt-4o
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: claude-3-5-sonnet-latest
|
||||
provider_id: anthropic
|
||||
provider_model_id: claude-3-5-sonnet-latest
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: gemini/gemini-1.5-flash
|
||||
provider_id: gemini
|
||||
provider_model_id: gemini/gemini-1.5-flash
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.3-70B-Instruct
|
||||
provider_id: groq
|
||||
provider_model_id: groq/llama-3.3-70b-versatile
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.1-405B-Instruct
|
||||
provider_id: together
|
||||
provider_model_id: meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo
|
||||
model_type: llm
|
||||
shields:
|
||||
- shield_id: meta-llama/Llama-Guard-3-8B
|
||||
vector_dbs: []
|
||||
datasets:
|
||||
- purpose: eval/messages-answer
|
||||
source:
|
||||
type: uri
|
||||
uri: huggingface://datasets/llamastack/simpleqa?split=train
|
||||
metadata: {}
|
||||
dataset_id: simpleqa
|
||||
- purpose: eval/messages-answer
|
||||
source:
|
||||
type: uri
|
||||
uri: huggingface://datasets/llamastack/mmlu_cot?split=test&name=all
|
||||
metadata: {}
|
||||
dataset_id: mmlu_cot
|
||||
- purpose: eval/messages-answer
|
||||
source:
|
||||
type: uri
|
||||
uri: huggingface://datasets/llamastack/gpqa_0shot_cot?split=test&name=gpqa_main
|
||||
metadata: {}
|
||||
dataset_id: gpqa_cot
|
||||
- purpose: eval/messages-answer
|
||||
source:
|
||||
type: uri
|
||||
uri: huggingface://datasets/llamastack/math_500?split=test
|
||||
metadata: {}
|
||||
dataset_id: math_500
|
||||
- purpose: eval/messages-answer
|
||||
source:
|
||||
type: uri
|
||||
uri: huggingface://datasets/llamastack/IfEval?split=train
|
||||
metadata: {}
|
||||
dataset_id: ifeval
|
||||
- purpose: eval/messages-answer
|
||||
source:
|
||||
type: uri
|
||||
uri: huggingface://datasets/llamastack/docvqa?split=val
|
||||
metadata: {}
|
||||
dataset_id: docvqa
|
||||
scoring_fns: []
|
||||
benchmarks:
|
||||
- dataset_id: simpleqa
|
||||
scoring_functions:
|
||||
- llm-as-judge::405b-simpleqa
|
||||
metadata: {}
|
||||
benchmark_id: meta-reference-simpleqa
|
||||
- dataset_id: mmlu_cot
|
||||
scoring_functions:
|
||||
- basic::regex_parser_multiple_choice_answer
|
||||
metadata: {}
|
||||
benchmark_id: meta-reference-mmlu-cot
|
||||
- dataset_id: gpqa_cot
|
||||
scoring_functions:
|
||||
- basic::regex_parser_multiple_choice_answer
|
||||
metadata: {}
|
||||
benchmark_id: meta-reference-gpqa-cot
|
||||
- dataset_id: math_500
|
||||
scoring_functions:
|
||||
- basic::regex_parser_math_response
|
||||
metadata: {}
|
||||
benchmark_id: meta-reference-math-500
|
||||
- dataset_id: ifeval
|
||||
scoring_functions:
|
||||
- basic::ifeval
|
||||
metadata: {}
|
||||
benchmark_id: meta-reference-ifeval
|
||||
- dataset_id: docvqa
|
||||
scoring_functions:
|
||||
- basic::docvqa
|
||||
metadata: {}
|
||||
benchmark_id: meta-reference-docvqa
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
- toolgroup_id: builtin::rag
|
||||
provider_id: rag-runtime
|
||||
server:
|
||||
port: 8321
|
||||
|
|
@ -1,248 +0,0 @@
|
|||
version: 2
|
||||
image_name: starter-gpu
|
||||
apis:
|
||||
- agents
|
||||
- batches
|
||||
- datasetio
|
||||
- eval
|
||||
- files
|
||||
- inference
|
||||
- post_training
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
|
||||
providers:
|
||||
inference:
|
||||
- provider_id: ${env.CEREBRAS_API_KEY:+cerebras}
|
||||
provider_type: remote::cerebras
|
||||
config:
|
||||
base_url: https://api.cerebras.ai
|
||||
api_key: ${env.CEREBRAS_API_KEY:=}
|
||||
- provider_id: ${env.OLLAMA_URL:+ollama}
|
||||
provider_type: remote::ollama
|
||||
config:
|
||||
url: ${env.OLLAMA_URL:=http://localhost:11434}
|
||||
- provider_id: ${env.VLLM_URL:+vllm}
|
||||
provider_type: remote::vllm
|
||||
config:
|
||||
url: ${env.VLLM_URL:=}
|
||||
max_tokens: ${env.VLLM_MAX_TOKENS:=4096}
|
||||
api_token: ${env.VLLM_API_TOKEN:=fake}
|
||||
tls_verify: ${env.VLLM_TLS_VERIFY:=true}
|
||||
- provider_id: ${env.TGI_URL:+tgi}
|
||||
provider_type: remote::tgi
|
||||
config:
|
||||
url: ${env.TGI_URL:=}
|
||||
- provider_id: fireworks
|
||||
provider_type: remote::fireworks
|
||||
config:
|
||||
url: https://api.fireworks.ai/inference/v1
|
||||
api_key: ${env.FIREWORKS_API_KEY:=}
|
||||
- provider_id: together
|
||||
provider_type: remote::together
|
||||
config:
|
||||
url: https://api.together.xyz/v1
|
||||
api_key: ${env.TOGETHER_API_KEY:=}
|
||||
- provider_id: bedrock
|
||||
provider_type: remote::bedrock
|
||||
- provider_id: ${env.NVIDIA_API_KEY:+nvidia}
|
||||
provider_type: remote::nvidia
|
||||
config:
|
||||
url: ${env.NVIDIA_BASE_URL:=https://integrate.api.nvidia.com}
|
||||
api_key: ${env.NVIDIA_API_KEY:=}
|
||||
append_api_version: ${env.NVIDIA_APPEND_API_VERSION:=True}
|
||||
- provider_id: openai
|
||||
provider_type: remote::openai
|
||||
config:
|
||||
api_key: ${env.OPENAI_API_KEY:=}
|
||||
base_url: ${env.OPENAI_BASE_URL:=https://api.openai.com/v1}
|
||||
- provider_id: anthropic
|
||||
provider_type: remote::anthropic
|
||||
config:
|
||||
api_key: ${env.ANTHROPIC_API_KEY:=}
|
||||
- provider_id: gemini
|
||||
provider_type: remote::gemini
|
||||
config:
|
||||
api_key: ${env.GEMINI_API_KEY:=}
|
||||
- provider_id: ${env.VERTEX_AI_PROJECT:+vertexai}
|
||||
provider_type: remote::vertexai
|
||||
config:
|
||||
project: ${env.VERTEX_AI_PROJECT:=}
|
||||
location: ${env.VERTEX_AI_LOCATION:=us-central1}
|
||||
- provider_id: groq
|
||||
provider_type: remote::groq
|
||||
config:
|
||||
url: https://api.groq.com
|
||||
api_key: ${env.GROQ_API_KEY:=}
|
||||
- provider_id: sambanova
|
||||
provider_type: remote::sambanova
|
||||
config:
|
||||
url: https://api.sambanova.ai/v1
|
||||
api_key: ${env.SAMBANOVA_API_KEY:=}
|
||||
- provider_id: ${env.AZURE_API_KEY:+azure}
|
||||
provider_type: remote::azure
|
||||
config:
|
||||
api_key: ${env.AZURE_API_KEY:=}
|
||||
api_base: ${env.AZURE_API_BASE:=}
|
||||
api_version: ${env.AZURE_API_VERSION:=}
|
||||
api_type: ${env.AZURE_API_TYPE:=}
|
||||
- provider_id: sentence-transformers
|
||||
provider_type: inline::sentence-transformers
|
||||
vector_io:
|
||||
- provider_id: faiss
|
||||
provider_type: inline::faiss
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/faiss_store.db
|
||||
- provider_id: sqlite-vec
|
||||
provider_type: inline::sqlite-vec
|
||||
config:
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/sqlite_vec.db
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/sqlite_vec_registry.db
|
||||
- provider_id: ${env.MILVUS_URL:+milvus}
|
||||
provider_type: inline::milvus
|
||||
config:
|
||||
db_path: ${env.MILVUS_DB_PATH:=~/.llama/distributions/starter-gpu}/milvus.db
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/milvus_registry.db
|
||||
- provider_id: ${env.CHROMADB_URL:+chromadb}
|
||||
provider_type: remote::chromadb
|
||||
config:
|
||||
url: ${env.CHROMADB_URL:=}
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu/}/chroma_remote_registry.db
|
||||
- provider_id: ${env.PGVECTOR_DB:+pgvector}
|
||||
provider_type: remote::pgvector
|
||||
config:
|
||||
host: ${env.PGVECTOR_HOST:=localhost}
|
||||
port: ${env.PGVECTOR_PORT:=5432}
|
||||
db: ${env.PGVECTOR_DB:=}
|
||||
user: ${env.PGVECTOR_USER:=}
|
||||
password: ${env.PGVECTOR_PASSWORD:=}
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/pgvector_registry.db
|
||||
files:
|
||||
- provider_id: meta-reference-files
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/starter-gpu/files}
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/files_metadata.db
|
||||
safety:
|
||||
- provider_id: llama-guard
|
||||
provider_type: inline::llama-guard
|
||||
config:
|
||||
excluded_categories: []
|
||||
- provider_id: code-scanner
|
||||
provider_type: inline::code-scanner
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
post_training:
|
||||
- provider_id: huggingface-gpu
|
||||
provider_type: inline::huggingface-gpu
|
||||
config:
|
||||
checkpoint_format: huggingface
|
||||
distributed_backend: null
|
||||
device: cpu
|
||||
dpo_output_dir: ~/.llama/distributions/starter-gpu/dpo_output
|
||||
eval:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/meta_reference_eval.db
|
||||
datasetio:
|
||||
- provider_id: huggingface
|
||||
provider_type: remote::huggingface
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/huggingface_datasetio.db
|
||||
- provider_id: localfs
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/localfs_datasetio.db
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
- provider_id: llm-as-judge
|
||||
provider_type: inline::llm-as-judge
|
||||
- provider_id: braintrust
|
||||
provider_type: inline::braintrust
|
||||
config:
|
||||
openai_api_key: ${env.OPENAI_API_KEY:=}
|
||||
tool_runtime:
|
||||
- provider_id: brave-search
|
||||
provider_type: remote::brave-search
|
||||
config:
|
||||
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: tavily-search
|
||||
provider_type: remote::tavily-search
|
||||
config:
|
||||
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
- provider_id: model-context-protocol
|
||||
provider_type: remote::model-context-protocol
|
||||
batches:
|
||||
- provider_id: reference
|
||||
provider_type: inline::reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/batches.db
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/inference_store.db
|
||||
models: []
|
||||
shields:
|
||||
- shield_id: llama-guard
|
||||
provider_id: ${env.SAFETY_MODEL:+llama-guard}
|
||||
provider_shield_id: ${env.SAFETY_MODEL:=}
|
||||
- shield_id: code-scanner
|
||||
provider_id: ${env.CODE_SCANNER_MODEL:+code-scanner}
|
||||
provider_shield_id: ${env.CODE_SCANNER_MODEL:=}
|
||||
vector_dbs: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
- toolgroup_id: builtin::rag
|
||||
provider_id: rag-runtime
|
||||
server:
|
||||
port: 8321
|
||||
|
|
@ -1,219 +0,0 @@
|
|||
version: 2
|
||||
image_name: watsonx
|
||||
apis:
|
||||
- agents
|
||||
- datasetio
|
||||
- eval
|
||||
- inference
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
|
||||
- files
|
||||
providers:
|
||||
inference:
|
||||
- provider_id: watsonx
|
||||
provider_type: remote::watsonx
|
||||
config:
|
||||
url: ${env.WATSONX_BASE_URL:=https://us-south.ml.cloud.ibm.com}
|
||||
api_key: ${env.WATSONX_API_KEY:=}
|
||||
project_id: ${env.WATSONX_PROJECT_ID:=}
|
||||
- provider_id: sentence-transformers
|
||||
provider_type: inline::sentence-transformers
|
||||
vector_io:
|
||||
- provider_id: faiss
|
||||
provider_type: inline::faiss
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/faiss_store.db
|
||||
safety:
|
||||
- provider_id: llama-guard
|
||||
provider_type: inline::llama-guard
|
||||
config:
|
||||
excluded_categories: []
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
eval:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/meta_reference_eval.db
|
||||
datasetio:
|
||||
- provider_id: huggingface
|
||||
provider_type: remote::huggingface
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/huggingface_datasetio.db
|
||||
- provider_id: localfs
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/localfs_datasetio.db
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
- provider_id: llm-as-judge
|
||||
provider_type: inline::llm-as-judge
|
||||
- provider_id: braintrust
|
||||
provider_type: inline::braintrust
|
||||
config:
|
||||
openai_api_key: ${env.OPENAI_API_KEY:=}
|
||||
tool_runtime:
|
||||
- provider_id: brave-search
|
||||
provider_type: remote::brave-search
|
||||
config:
|
||||
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: tavily-search
|
||||
provider_type: remote::tavily-search
|
||||
config:
|
||||
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
- provider_id: model-context-protocol
|
||||
provider_type: remote::model-context-protocol
|
||||
files:
|
||||
- provider_id: meta-reference-files
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/watsonx/files}
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/files_metadata.db
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/watsonx}/inference_store.db
|
||||
models:
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-3-3-70b-instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-3-70b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.3-70B-Instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-3-70b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-2-13b-chat
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-2-13b-chat
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-2-13b
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-2-13b-chat
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-3-1-70b-instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-1-70b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.1-70B-Instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-1-70b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-3-1-8b-instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-1-8b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.1-8B-Instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-1-8b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-3-2-11b-vision-instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-11b-vision-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.2-11B-Vision-Instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-11b-vision-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-3-2-1b-instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-1b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.2-1B-Instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-1b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-3-2-3b-instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-3b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.2-3B-Instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-3b-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-3-2-90b-vision-instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-90b-vision-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-3.2-90B-Vision-Instruct
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-3-2-90b-vision-instruct
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/llama-guard-3-11b-vision
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-guard-3-11b-vision
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: meta-llama/Llama-Guard-3-11B-Vision
|
||||
provider_id: watsonx
|
||||
provider_model_id: meta-llama/llama-guard-3-11b-vision
|
||||
model_type: llm
|
||||
- metadata:
|
||||
embedding_dimension: 384
|
||||
model_id: all-MiniLM-L6-v2
|
||||
provider_id: sentence-transformers
|
||||
model_type: embedding
|
||||
shields: []
|
||||
vector_dbs: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
- toolgroup_id: builtin::rag
|
||||
provider_id: rag-runtime
|
||||
server:
|
||||
port: 8321
|
||||
|
|
@ -1,184 +0,0 @@
|
|||
"""
|
||||
Coin Change - Interview Practice Problem
|
||||
|
||||
Problem: You are given an integer array coins representing coins of different denominations
|
||||
and an integer amount representing a total amount of money.
|
||||
|
||||
Return the fewest number of coins that you need to make up that amount.
|
||||
If that amount of money cannot be made up by any combination of the coins, return -1.
|
||||
|
||||
You may assume that you have an infinite number of each kind of coin.
|
||||
|
||||
Example 1:
|
||||
Input: coins = [1,3,4], amount = 6
|
||||
Output: 2
|
||||
Explanation: 6 = 3 + 3
|
||||
|
||||
Example 2:
|
||||
Input: coins = [2], amount = 3
|
||||
Output: -1
|
||||
|
||||
Example 3:
|
||||
Input: coins = [1], amount = 0
|
||||
Output: 0
|
||||
|
||||
Constraints:
|
||||
- 1 <= coins.length <= 12
|
||||
- 1 <= coins[i] <= 2^31 - 1
|
||||
- 0 <= amount <= 10^4
|
||||
"""
|
||||
|
||||
|
||||
def coinChange(coins, amount):
|
||||
"""
|
||||
Find the minimum number of coins needed to make the given amount.
|
||||
|
||||
Args:
|
||||
coins: List[int] - denominations of coins available
|
||||
amount: int - target amount to make
|
||||
|
||||
Returns:
|
||||
int - minimum number of coins needed, or -1 if impossible
|
||||
|
||||
Time Complexity Goal: O(amount * len(coins))
|
||||
Space Complexity Goal: O(amount)
|
||||
|
||||
Hint: This is a classic Dynamic Programming problem!
|
||||
Think about: What's the minimum coins needed for each amount from 0 to target?
|
||||
"""
|
||||
min_coins = [-1 for _ in range(amount) + 1]
|
||||
min_coins[0] = 0
|
||||
for cur_amount in range(amount) + 1:
|
||||
num = [amount + 1 for _ in coins]
|
||||
for i, coin in enumerate(coins):
|
||||
hist = cur_amount - coin
|
||||
if hist >= 0 and min_coins[hist] != -1
|
||||
num[i] = min_coins[]
|
||||
|
||||
|
||||
|
||||
def test_coin_change():
|
||||
"""Comprehensive test cases for coinChange function"""
|
||||
|
||||
print("=" * 60)
|
||||
print("COIN CHANGE - TEST CASES")
|
||||
print("=" * 60)
|
||||
|
||||
# Test Case 1: Basic example from problem description
|
||||
print("\nTest Case 1: Basic Example")
|
||||
coins1 = [1, 3, 4]
|
||||
amount1 = 6
|
||||
result1 = coinChange(coins1, amount1)
|
||||
expected1 = 2 # 3 + 3
|
||||
print(f"Coins: {coins1}, Amount: {amount1}")
|
||||
print(f"Result: {result1}, Expected: {expected1}")
|
||||
assert result1 == expected1, f"Test 1 failed: got {result1}, expected {expected1}"
|
||||
print("✅ Test 1 PASSED")
|
||||
|
||||
# Test Case 2: Impossible case
|
||||
print("\nTest Case 2: Impossible Case")
|
||||
coins2 = [2]
|
||||
amount2 = 3
|
||||
result2 = coinChange(coins2, amount2)
|
||||
expected2 = -1
|
||||
print(f"Coins: {coins2}, Amount: {amount2}")
|
||||
print(f"Result: {result2}, Expected: {expected2}")
|
||||
assert result2 == expected2, f"Test 2 failed: got {result2}, expected {expected2}"
|
||||
print("✅ Test 2 PASSED")
|
||||
|
||||
# Test Case 3: Zero amount
|
||||
print("\nTest Case 3: Zero Amount")
|
||||
coins3 = [1]
|
||||
amount3 = 0
|
||||
result3 = coinChange(coins3, amount3)
|
||||
expected3 = 0
|
||||
print(f"Coins: {coins3}, Amount: {amount3}")
|
||||
print(f"Result: {result3}, Expected: {expected3}")
|
||||
assert result3 == expected3, f"Test 3 failed: got {result3}, expected {expected3}"
|
||||
print("✅ Test 3 PASSED")
|
||||
|
||||
# Test Case 4: Single coin solution
|
||||
print("\nTest Case 4: Single Coin Solution")
|
||||
coins4 = [1, 3, 4]
|
||||
amount4 = 4
|
||||
result4 = coinChange(coins4, amount4)
|
||||
expected4 = 1 # Just use coin 4
|
||||
print(f"Coins: {coins4}, Amount: {amount4}")
|
||||
print(f"Result: {result4}, Expected: {expected4}")
|
||||
assert result4 == expected4, f"Test 4 failed: got {result4}, expected {expected4}"
|
||||
print("✅ Test 4 PASSED")
|
||||
|
||||
# Test Case 5: Greedy fails, DP succeeds
|
||||
print("\nTest Case 5: Greedy Algorithm Fails")
|
||||
coins5 = [1, 3, 4]
|
||||
amount5 = 6
|
||||
result5 = coinChange(coins5, amount5)
|
||||
expected5 = 2 # 3 + 3, not 4 + 1 + 1 (greedy would give 3)
|
||||
print(f"Coins: {coins5}, Amount: {amount5}")
|
||||
print(f"Result: {result5}, Expected: {expected5}")
|
||||
print("Note: Greedy (largest first) would give 4+1+1=3 coins, but optimal is 3+3=2 coins")
|
||||
assert result5 == expected5, f"Test 5 failed: got {result5}, expected {expected5}"
|
||||
print("✅ Test 5 PASSED")
|
||||
|
||||
# Test Case 6: Large amount (performance test)
|
||||
print("\nTest Case 6: Large Amount (Performance Test)")
|
||||
coins6 = [1, 5, 10, 25]
|
||||
amount6 = 67
|
||||
result6 = coinChange(coins6, amount6)
|
||||
expected6 = 5 # 25 + 25 + 10 + 5 + 1 + 1 = 67
|
||||
print(f"Coins: {coins6}, Amount: {amount6}")
|
||||
print(f"Result: {result6}, Expected: {expected6}")
|
||||
assert result6 == expected6, f"Test 6 failed: got {result6}, expected {expected6}"
|
||||
print("✅ Test 6 PASSED")
|
||||
|
||||
# Test Case 7: All ones (edge case)
|
||||
print("\nTest Case 7: Only Coin Value 1")
|
||||
coins7 = [1]
|
||||
amount7 = 5
|
||||
result7 = coinChange(coins7, amount7)
|
||||
expected7 = 5 # 1 + 1 + 1 + 1 + 1
|
||||
print(f"Coins: {coins7}, Amount: {amount7}")
|
||||
print(f"Result: {result7}, Expected: {expected7}")
|
||||
assert result7 == expected7, f"Test 7 failed: got {result7}, expected {expected7}"
|
||||
print("✅ Test 7 PASSED")
|
||||
|
||||
# Test Case 8: Complex case with many coins
|
||||
print("\nTest Case 8: Complex Case")
|
||||
coins8 = [2, 3, 5]
|
||||
amount8 = 9
|
||||
result8 = coinChange(coins8, amount8)
|
||||
expected8 = 3 # 3 + 3 + 3
|
||||
print(f"Coins: {coins8}, Amount: {amount8}")
|
||||
print(f"Result: {result8}, Expected: {expected8}")
|
||||
assert result8 == expected8, f"Test 8 failed: got {result8}, expected {expected8}"
|
||||
print("✅ Test 8 PASSED")
|
||||
|
||||
# Test Case 9: Impossible with multiple coins
|
||||
print("\nTest Case 9: Impossible with Multiple Coins")
|
||||
coins9 = [3, 5]
|
||||
amount9 = 1
|
||||
result9 = coinChange(coins9, amount9)
|
||||
expected9 = -1
|
||||
print(f"Coins: {coins9}, Amount: {amount9}")
|
||||
print(f"Result: {result9}, Expected: {expected9}")
|
||||
assert result9 == expected9, f"Test 9 failed: got {result9}, expected {expected9}"
|
||||
print("✅ Test 9 PASSED")
|
||||
|
||||
# Test Case 10: Large performance test
|
||||
print("\nTest Case 10: Large Performance Test")
|
||||
coins10 = [1, 2, 5, 10, 20, 50]
|
||||
amount10 = 1000
|
||||
result10 = coinChange(coins10, amount10)
|
||||
expected10 = 20 # 20 coins of 50 each
|
||||
print(f"Coins: {coins10}, Amount: {amount10}")
|
||||
print(f"Result: {result10}, Expected: {expected10}")
|
||||
assert result10 == expected10, f"Test 10 failed: got {result10}, expected {expected10}"
|
||||
print("✅ Test 10 PASSED")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("🎉 ALL TESTS PASSED! Great job!")
|
||||
print("=" * 60)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_coin_change()
|
||||
|
|
@ -1,243 +0,0 @@
|
|||
from collections import defaultdict
|
||||
|
||||
|
||||
def guess_next_character(mystery_word_pattern, guessed_characters, word_pool):
|
||||
"""
|
||||
Returns:
|
||||
str: Single character that is most likely to be in the mystery word,
|
||||
or None if no good guess can be made
|
||||
"""
|
||||
num_chars = len(mystery_word_pattern)
|
||||
correct_positions = {i: c for i, c in enumerate(mystery_word_pattern) if c != "_"}
|
||||
char_counts_by_position = [defaultdict(int) for _ in range(num_chars)]
|
||||
|
||||
for word in word_pool:
|
||||
wordlen = len(word)
|
||||
matches = True
|
||||
for i, c in correct_positions.items():
|
||||
if i < wordlen and word[i] != c:
|
||||
matches = False
|
||||
break
|
||||
if not matches:
|
||||
continue
|
||||
|
||||
for j, c in enumerate(word):
|
||||
if j >= num_chars:
|
||||
continue
|
||||
if c in guessed_characters:
|
||||
continue
|
||||
if mystery_word_pattern[j] != "_":
|
||||
continue
|
||||
char_counts_by_position[j][c] += 1
|
||||
|
||||
max_count = 0
|
||||
char = None
|
||||
for counts in char_counts_by_position:
|
||||
for c, v in counts.items():
|
||||
if v > max_count:
|
||||
max_count = v
|
||||
char = c
|
||||
return char
|
||||
|
||||
|
||||
# Test cases
|
||||
def test_guess_next_character():
|
||||
"""Test cases for the hangman character guesser"""
|
||||
|
||||
# Test case 1: Basic case with clear winner
|
||||
pattern = "_at"
|
||||
guessed = ["a", "t"]
|
||||
pool = ["cat", "bat", "hat", "rat", "mat"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Any of 'c', 'b', 'h', 'r', 'm' would be valid since they all appear once
|
||||
assert result in ["c", "b", "h", "r", "m"], f"Expected one of 'c','b','h','r','m', got {result}"
|
||||
|
||||
# Test case 2: Some characters already guessed
|
||||
pattern = "_at"
|
||||
guessed = ["a", "t", "c", "b"]
|
||||
pool = ["cat", "bat", "hat", "rat", "mat"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result in ["h", "r", "m"], f"Expected one of 'h','r','m', got {result}"
|
||||
|
||||
# Test case 3: Multiple missing positions
|
||||
pattern = "_a_e"
|
||||
guessed = ["a", "e"]
|
||||
pool = ["cake", "bake", "lake", "make", "take", "wake", "came", "name", "game", "same"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should return most frequent character in missing positions
|
||||
assert isinstance(result, str) and len(result) == 1, f"Expected single character, got {result}"
|
||||
|
||||
# Test case 4: Word pool doesn't match pattern (should filter)
|
||||
pattern = "_at"
|
||||
guessed = ["a", "t"]
|
||||
pool = ["cat", "dog", "bat", "rat", "hat"] # "dog" doesn't match the pattern
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result in ["c", "b", "r", "h"], f"Expected one of 'c','b','r','h', got {result}"
|
||||
|
||||
# Test case 5: All characters in matching words already guessed
|
||||
pattern = "_at"
|
||||
guessed = ["a", "t", "c", "b", "h", "r", "m"]
|
||||
pool = ["cat", "bat", "hat", "rat", "mat"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result is None, f"Expected None when all characters guessed, got {result}"
|
||||
|
||||
# Test case 6: Single character missing
|
||||
pattern = "c_t"
|
||||
guessed = ["c", "t"]
|
||||
pool = ["cat", "cot", "cut", "cit"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should return most frequent vowel/character in position 1
|
||||
assert isinstance(result, str) and len(result) == 1, f"Expected single character, got {result}"
|
||||
|
||||
# Test case 7: Empty word pool
|
||||
pattern = "_at"
|
||||
guessed = ["a", "t"]
|
||||
pool = []
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result is None, f"Expected None for empty pool, got {result}"
|
||||
|
||||
# Test case 8: No matching words in pool
|
||||
pattern = "_at"
|
||||
guessed = ["a", "t"]
|
||||
pool = ["dog", "run", "sun"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result is None, f"Expected None when no words match pattern, got {result}"
|
||||
|
||||
# Test case 9: Longer word with multiple gaps
|
||||
pattern = "_o_er"
|
||||
guessed = ["o", "e", "r"]
|
||||
pool = ["power", "tower", "lower", "cover", "hover", "mower", "boxer", "poker"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert isinstance(result, str) and len(result) == 1, f"Expected single character, got {result}"
|
||||
|
||||
# Test case 10: Case sensitivity
|
||||
pattern = "_at"
|
||||
guessed = ["a", "t"]
|
||||
pool = ["Cat", "BAT", "hat"] # Mixed case
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should handle case appropriately
|
||||
assert result is not None, f"Expected a character, got {result}"
|
||||
|
||||
# Test case 11: Tie-breaking - multiple characters with same frequency
|
||||
pattern = "_a_"
|
||||
guessed = ["a"]
|
||||
pool = ["cat", "bat", "had", "bag"] # c,b,h,g all appear once in pos 0; t,t,d,g in pos 2
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should return one of the valid characters (implementation dependent)
|
||||
assert result is not None and result not in guessed, f"Expected unguessed character, got {result}"
|
||||
|
||||
# Test case 12: Complex pattern with repeated characters in word
|
||||
pattern = "_oo_"
|
||||
guessed = ["o"]
|
||||
pool = ["book", "look", "took", "cook", "hook", "noon", "boom", "doom"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result is not None and result != "o", f"Expected character other than 'o', got {result}"
|
||||
|
||||
# Test case 13: Very long word with sparse information
|
||||
pattern = "___e____i__"
|
||||
guessed = ["e", "i"]
|
||||
pool = ["programming", "engineering", "mathematics", "development"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Only "programming" and "engineering" match the pattern
|
||||
assert result is not None, f"Expected a character, got {result}"
|
||||
|
||||
# Test case 14: Word with all same length but different patterns
|
||||
pattern = "_a__a"
|
||||
guessed = ["a"]
|
||||
pool = ["mamma", "drama", "llama", "karma", "panda"] # "panda" doesn't match
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should only consider mamma, drama, llama, karma
|
||||
assert result is not None and result != "a", f"Expected character other than 'a', got {result}"
|
||||
|
||||
# Test case 15: Single letter word
|
||||
pattern = "_"
|
||||
guessed = []
|
||||
pool = ["a", "I", "o"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result in ["a", "I", "o"], f"Expected one of 'a','I','o', got {result}"
|
||||
|
||||
# Test case 16: Almost complete word - only one missing
|
||||
pattern = "almos_"
|
||||
guessed = ["a", "l", "m", "o", "s"]
|
||||
pool = ["almost", "almond"] # "almond" doesn't match pattern
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result == "t", f"Expected 't', got {result}"
|
||||
|
||||
# Test case 17: Frequency analysis with position weighting
|
||||
pattern = "_e__e_"
|
||||
guessed = ["e"]
|
||||
pool = ["better", "letter", "pepper", "keeper", "helper", "member"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should find most frequent character across all missing positions
|
||||
assert result is not None and result != "e", f"Expected character other than 'e', got {result}"
|
||||
|
||||
# Test case 18: Words with different lengths in pool (should filter by length)
|
||||
pattern = "___"
|
||||
guessed = []
|
||||
pool = ["cat", "dog", "fox", "car", "bar", "bat", "run"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should only consider 3-letter words: cat, dog, fox, car, bar, bat, run
|
||||
assert result is not None, f"Expected a character, got {result}"
|
||||
|
||||
# Test case 19: All positions filled except one, but multiple valid completions
|
||||
pattern = "c_r"
|
||||
guessed = ["c", "r"]
|
||||
pool = ["car", "cor", "cur", "cir"] # All valid completions
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result in ["a", "o", "u", "i"], f"Expected one of 'a','o','u','i', got {result}"
|
||||
|
||||
# Test case 20: Pattern with numbers/special chars (edge case)
|
||||
pattern = "_a_"
|
||||
guessed = ["a"]
|
||||
pool = ["1a2", "3a4", "cat", "bat"] # Mix of alphanumeric and letters
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# Should handle all valid characters
|
||||
assert result is not None, f"Expected a character, got {result}"
|
||||
|
||||
# Test case 21: Very large frequency difference
|
||||
pattern = "_a_"
|
||||
guessed = ["a"]
|
||||
pool = ["cat"] * 100 + ["bat", "hat", "rat"] # 'c' appears 100 times, others once each
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
assert result == "c", f"Expected 'c' due to high frequency, got {result}"
|
||||
|
||||
# Test case 22: Pattern where some positions have no valid characters
|
||||
pattern = "_x_"
|
||||
guessed = [
|
||||
"x",
|
||||
"a",
|
||||
"b",
|
||||
"c",
|
||||
"d",
|
||||
"e",
|
||||
"f",
|
||||
"g",
|
||||
"h",
|
||||
"i",
|
||||
"j",
|
||||
"k",
|
||||
"l",
|
||||
"m",
|
||||
"n",
|
||||
"o",
|
||||
"p",
|
||||
"q",
|
||||
"r",
|
||||
"s",
|
||||
"t",
|
||||
"u",
|
||||
"v",
|
||||
"w",
|
||||
"y",
|
||||
"z",
|
||||
]
|
||||
pool = ["axe", "fox", "box", "six"]
|
||||
result = guess_next_character(pattern, guessed, pool)
|
||||
# All common letters guessed, should return None or a less common letter
|
||||
assert result is None or result not in guessed, f"Unexpected result: {result}"
|
||||
|
||||
print("All test cases passed!")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_guess_next_character()
|
||||
|
|
@ -1,140 +0,0 @@
|
|||
"""
|
||||
Rotate Image (Matrix) - Interview Practice Problem
|
||||
|
||||
Problem: Given an n x n 2D matrix representing an image, rotate it by 90 degrees clockwise in-place.
|
||||
You have to rotate the image in-place, which means you have to modify the input 2D matrix directly.
|
||||
DO NOT allocate another 2D matrix and do the rotation.
|
||||
|
||||
Example:
|
||||
Input: [[1,2,3],
|
||||
[4,5,6],
|
||||
[7,8,9]]
|
||||
|
||||
Output: [[7,4,1],
|
||||
[8,5,2],
|
||||
[9,6,3]]
|
||||
|
||||
Constraints:
|
||||
- n == matrix.length == matrix[i].length
|
||||
- 1 <= n <= 20
|
||||
- -1000 <= matrix[i][j] <= 1000
|
||||
"""
|
||||
|
||||
|
||||
def rotate(matrix):
|
||||
"""
|
||||
Rotate the matrix 90 degrees clockwise in-place.
|
||||
|
||||
Args:
|
||||
matrix: List[List[int]] - n x n 2D matrix
|
||||
|
||||
Returns:
|
||||
None - Do not return anything, modify matrix in-place instead.
|
||||
|
||||
Time Complexity Goal: O(n^2)
|
||||
Space Complexity Goal: O(1)
|
||||
"""
|
||||
a = matrix
|
||||
n = len(a[0])
|
||||
|
||||
# first swap against one diagonal so a(i, j) -> a(n - j - 1, n - i - 1)
|
||||
for i in range(0, n):
|
||||
for j in range(0, n - i):
|
||||
t = a[i][j]
|
||||
a[i][j] = a[n - j - 1][n - i - 1]
|
||||
a[n - j - 1][n - i - 1] = t
|
||||
|
||||
# now flip across horizontal line
|
||||
for i in range(0, n // 2):
|
||||
for j in range(0, n):
|
||||
t = a[i][j]
|
||||
a[i][j] = a[n - i - 1][j]
|
||||
a[n - i - 1][j] = t
|
||||
|
||||
|
||||
def print_matrix(matrix, title="Matrix"):
|
||||
"""Helper function to print matrix in a readable format"""
|
||||
print(f"\n{title}:")
|
||||
for row in matrix:
|
||||
print(row)
|
||||
|
||||
|
||||
def test_rotate():
|
||||
"""Comprehensive test cases for rotate function"""
|
||||
|
||||
print("=" * 60)
|
||||
print("ROTATE IMAGE - TEST CASES")
|
||||
print("=" * 60)
|
||||
|
||||
# Test Case 1: 3x3 matrix (basic example)
|
||||
print("\nTest Case 1: 3x3 Matrix")
|
||||
matrix1 = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
|
||||
expected1 = [[7, 4, 1], [8, 5, 2], [9, 6, 3]]
|
||||
print_matrix(matrix1, "Before rotation")
|
||||
rotate(matrix1)
|
||||
print_matrix(matrix1, "After rotation")
|
||||
print_matrix(expected1, "Expected")
|
||||
assert matrix1 == expected1, f"Test 1 failed: got {matrix1}, expected {expected1}"
|
||||
print("✅ Test 1 PASSED")
|
||||
|
||||
# Test Case 2: 1x1 matrix (edge case)
|
||||
print("\nTest Case 2: 1x1 Matrix (Edge Case)")
|
||||
matrix2 = [[42]]
|
||||
expected2 = [[42]]
|
||||
print_matrix(matrix2, "Before rotation")
|
||||
rotate(matrix2)
|
||||
print_matrix(matrix2, "After rotation")
|
||||
assert matrix2 == expected2, f"Test 2 failed: got {matrix2}, expected {expected2}"
|
||||
print("✅ Test 2 PASSED")
|
||||
|
||||
# Test Case 3: 2x2 matrix
|
||||
print("\nTest Case 3: 2x2 Matrix")
|
||||
matrix3 = [[1, 2], [3, 4]]
|
||||
expected3 = [[3, 1], [4, 2]]
|
||||
print_matrix(matrix3, "Before rotation")
|
||||
rotate(matrix3)
|
||||
print_matrix(matrix3, "After rotation")
|
||||
print_matrix(expected3, "Expected")
|
||||
assert matrix3 == expected3, f"Test 3 failed: got {matrix3}, expected {expected3}"
|
||||
print("✅ Test 3 PASSED")
|
||||
|
||||
# Test Case 4: 4x4 matrix (larger matrix)
|
||||
print("\nTest Case 4: 4x4 Matrix")
|
||||
matrix4 = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]
|
||||
expected4 = [[13, 9, 5, 1], [14, 10, 6, 2], [15, 11, 7, 3], [16, 12, 8, 4]]
|
||||
print_matrix(matrix4, "Before rotation")
|
||||
rotate(matrix4)
|
||||
print_matrix(matrix4, "After rotation")
|
||||
print_matrix(expected4, "Expected")
|
||||
assert matrix4 == expected4, f"Test 4 failed: got {matrix4}, expected {expected4}"
|
||||
print("✅ Test 4 PASSED")
|
||||
|
||||
# Test Case 5: Matrix with negative numbers
|
||||
print("\nTest Case 5: Matrix with Negative Numbers")
|
||||
matrix5 = [[-1, -2, -3], [-4, -5, -6], [-7, -8, -9]]
|
||||
expected5 = [[-7, -4, -1], [-8, -5, -2], [-9, -6, -3]]
|
||||
print_matrix(matrix5, "Before rotation")
|
||||
rotate(matrix5)
|
||||
print_matrix(matrix5, "After rotation")
|
||||
print_matrix(expected5, "Expected")
|
||||
assert matrix5 == expected5, f"Test 5 failed: got {matrix5}, expected {expected5}"
|
||||
print("✅ Test 5 PASSED")
|
||||
|
||||
# Test Case 6: 5x5 matrix (odd dimension, complexity test)
|
||||
print("\nTest Case 6: 5x5 Matrix (Complexity Test)")
|
||||
matrix6 = [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15], [16, 17, 18, 19, 20], [21, 22, 23, 24, 25]]
|
||||
expected6 = [[21, 16, 11, 6, 1], [22, 17, 12, 7, 2], [23, 18, 13, 8, 3], [24, 19, 14, 9, 4], [25, 20, 15, 10, 5]]
|
||||
print_matrix(matrix6, "Before rotation")
|
||||
rotate(matrix6)
|
||||
print_matrix(matrix6, "After rotation")
|
||||
print_matrix(expected6, "Expected")
|
||||
assert matrix6 == expected6, f"Test 6 failed: got {matrix6}, expected {expected6}"
|
||||
print("✅ Test 6 PASSED")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("🎉 ALL TESTS PASSED! Great job!")
|
||||
print("=" * 60)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_rotate()
|
||||
Loading…
Add table
Add a link
Reference in a new issue