diff --git a/pyproject.toml b/pyproject.toml index 505f3556..ad4149de 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -90,6 +90,9 @@ dev-dependencies = [ "hatch>=1.14.1", "ruff>=0.12.1", "pyright>=1.1.403", + "pytest>=8.4.1", + "nbval>=0.11.0", + "pytest-xdist>=3.8.0", ] [tool.uv.sources] diff --git a/scripts/run_checks.sh b/scripts/run_checks.sh index ce2aebf0..79ff3671 100755 --- a/scripts/run_checks.sh +++ b/scripts/run_checks.sh @@ -27,6 +27,7 @@ fi # Track if any checks fail CHECKS_PASSED=true TYPECHECK_FAILED=false +TESTS_FAILED=false # Run format check echo "๐Ÿ“ Checking code formatting..." @@ -75,7 +76,7 @@ echo # Run type checking (Pyright) echo "๐Ÿง  Running type checking..." TMP_PYRIGHT_JSON=$(mktemp) -echo " Running: uv run pyright --outputjson src" +echo " Running: uv run pyright --outputjson src tests" # Capture JSON output quietly regardless of success/failure if uv run pyright --outputjson src > "$TMP_PYRIGHT_JSON" 2>/dev/null; then : # success, continue @@ -125,6 +126,66 @@ fi rm -f "$TMP_PYRIGHT_JSON" echo +# Run tests +echo "๐Ÿงช Running unit tests..." +echo " Running: uv run pytest --nbval tests/unit" + +# Capture pytest output quietly to parse the summary +PYTEST_OUTPUT=$(mktemp) +if uv run pytest --nbval --tb=short tests/unit > "$PYTEST_OUTPUT" 2>&1; then + TEST_EXIT_CODE=0 +else + TEST_EXIT_CODE=$? +fi + +# Extract the test summary line (e.g., "===== 5 passed, 2 failed, 1 skipped in 3.45s =====") +# This regex captures various pytest summary formats +TEST_SUMMARY=$(grep -E "^=+ .*(passed|failed|error|skipped|xfailed|xpassed|warning).*=+$" "$PYTEST_OUTPUT" | tail -1) + +if [[ -n "$TEST_SUMMARY" ]]; then + # Parse the summary to extract counts + PASSED=$(echo "$TEST_SUMMARY" | grep -oE "[0-9]+ passed" | grep -oE "[0-9]+" || echo "0") + FAILED=$(echo "$TEST_SUMMARY" | grep -oE "[0-9]+ failed" | grep -oE "[0-9]+" || echo "0") + ERRORS=$(echo "$TEST_SUMMARY" | grep -oE "[0-9]+ error" | grep -oE "[0-9]+" || echo "0") + SKIPPED=$(echo "$TEST_SUMMARY" | grep -oE "[0-9]+ skipped" | grep -oE "[0-9]+" || echo "0") + WARNINGS=$(echo "$TEST_SUMMARY" | grep -oE "[0-9]+ warning" | grep -oE "[0-9]+" || echo "0") + XFAILED=$(echo "$TEST_SUMMARY" | grep -oE "[0-9]+ xfailed" | grep -oE "[0-9]+" || echo "0") + XPASSED=$(echo "$TEST_SUMMARY" | grep -oE "[0-9]+ xpassed" | grep -oE "[0-9]+" || echo "0") + + # Build detailed summary + DETAILS="" + [[ "$PASSED" != "0" ]] && DETAILS="${DETAILS}Passed: $PASSED" + [[ "$FAILED" != "0" ]] && DETAILS="${DETAILS:+$DETAILS, }Failed: $FAILED" + [[ "$ERRORS" != "0" ]] && DETAILS="${DETAILS:+$DETAILS, }Errors: $ERRORS" + [[ "$SKIPPED" != "0" ]] && DETAILS="${DETAILS:+$DETAILS, }Skipped: $SKIPPED" + [[ "$XFAILED" != "0" ]] && DETAILS="${DETAILS:+$DETAILS, }XFailed: $XFAILED" + [[ "$XPASSED" != "0" ]] && DETAILS="${DETAILS:+$DETAILS, }XPassed: $XPASSED" + [[ "$WARNINGS" != "0" ]] && DETAILS="${DETAILS:+$DETAILS, }Warnings: $WARNINGS" + + # Check if there were any failures or errors + if [[ "$FAILED" == "0" && "$ERRORS" == "0" && $TEST_EXIT_CODE -eq 0 ]]; then + echo -e "${GREEN}โœ… All tests passed${NC}" + [[ -n "$DETAILS" ]] && echo " $DETAILS" + else + echo -e "${RED}โŒ Tests failed${NC}" + [[ -n "$DETAILS" ]] && echo " $DETAILS" + CHECKS_PASSED=false + TESTS_FAILED=true + fi +else + # Fallback if we can't parse the summary + if [[ $TEST_EXIT_CODE -eq 0 ]]; then + echo -e "${GREEN}โœ… All unit tests passed${NC}" + else + echo -e "${RED}โŒ Some unit tests failed${NC}" + CHECKS_PASSED=false + TESTS_FAILED=true + fi +fi + +rm -f "$PYTEST_OUTPUT" +echo + # Check if uv.lock is in sync with pyproject.toml echo "๐Ÿ”’ Checking if uv.lock is up to date..." PRIMARY_EXTRAS=(--all-extras) @@ -201,9 +262,15 @@ if $CHECKS_PASSED; then else echo -e "${RED}โŒ Some checks failed${NC}" if [[ -z "$FIX_FLAG" ]]; then + # Show tips for each type of failure if $TYPECHECK_FAILED; then echo -e "๐Ÿ’ก Tip: Type errors can't be auto-fixed by --fix. Re-run ${YELLOW}uv run pyright src${NC} to see full diagnostics." - else + fi + if $TESTS_FAILED; then + echo -e "๐Ÿ’ก Tip: Test failures can't be auto-fixed by --fix. Re-run ${YELLOW}uv run pytest --nbval tests/unit${NC} to see full test output." + fi + # Show general fix tip if there are failures but not type/test specific ones + if ! $TYPECHECK_FAILED && ! $TESTS_FAILED; then echo -e "๐Ÿ’ก Tip: Run ${YELLOW}./scripts/run_checks.sh --fix${NC} to automatically fix some issues" fi fi diff --git a/src/art/local/backend.py b/src/art/local/backend.py index 1129326e..957e088e 100644 --- a/src/art/local/backend.py +++ b/src/art/local/backend.py @@ -42,20 +42,20 @@ from .. import dev from ..backend import Backend from ..model import Model, TrainableModel +from ..preprocessing.pack import ( + PackedTensors, + packed_tensors_from_tokenized_results, + packed_tensors_to_dir, + plot_packed_tensors, +) +from ..preprocessing.tokenize import tokenize_trajectory_groups from ..trajectories import Trajectory, TrajectoryGroup from ..types import Message, TrainConfig from ..utils import format_message, get_model_step from .checkpoints import ( delete_checkpoints, ) -from .pack import ( - PackedTensors, - packed_tensors_from_tokenized_results, - packed_tensors_to_dir, - plot_packed_tensors, -) from .service import ModelService -from .tokenize import tokenize_trajectory_groups class LocalBackend(Backend): diff --git a/src/art/local/service.py b/src/art/local/service.py index bcc7cb02..9aaf0e17 100644 --- a/src/art/local/service.py +++ b/src/art/local/service.py @@ -1,7 +1,7 @@ from typing import AsyncIterator, Protocol, runtime_checkable from .. import dev, types -from .pack import DiskPackedTensors +from ..preprocessing.pack import DiskPackedTensors @runtime_checkable diff --git a/src/art/preprocessing/__init__.py b/src/art/preprocessing/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/art/local/pack.py b/src/art/preprocessing/pack.py similarity index 100% rename from src/art/local/pack.py rename to src/art/preprocessing/pack.py diff --git a/src/art/local/tokenize.py b/src/art/preprocessing/tokenize.py similarity index 75% rename from src/art/local/tokenize.py rename to src/art/preprocessing/tokenize.py index 3bf355bb..e1500ba6 100644 --- a/src/art/local/tokenize.py +++ b/src/art/preprocessing/tokenize.py @@ -146,12 +146,18 @@ def tokenize_trajectory( tools=history.tools, # type: ignore ), ) - sentinal_token_id = max( + sentinal_start_token_id = max( set(range(cast(int, tokenizer.vocab_size))) - set(original_token_ids) ) - sentinal_token = tokenizer.decode(sentinal_token_id) - result = cast( - dict, + sentinal_end_token_id = max( + set(range(cast(int, tokenizer.vocab_size))) + - set(original_token_ids) + - {sentinal_start_token_id} + ) + sentinal_start_token = tokenizer.decode(sentinal_start_token_id) + sentinal_end_token = tokenizer.decode(sentinal_end_token_id) + token_ids = cast( + list[int], tokenizer.apply_chat_template( cast( list[dict], @@ -159,53 +165,54 @@ def tokenize_trajectory( ( message_or_choice if isinstance(message_or_choice, dict) + and not message_or_choice["role"] == "assistant" else { "role": "assistant", - "content": sentinal_token, + "content": f"{sentinal_start_token}{message_or_choice.get('content', None) if isinstance(message_or_choice, dict) else message_or_choice.message.content or ''}{sentinal_end_token}", } ) for message_or_choice in messages_and_choices ], ), tools=history.tools, # type: ignore - return_dict=True, - return_assistant_token_mask=allow_training_without_logprobs, ), ) - token_ids: list[int] = result["input_ids"] - assistant_mask: list[int] = ( - result["attention_mask"] - if allow_training_without_logprobs - else [0] * len(token_ids) - ) + assistant_mask: list[int] = [0] * len(token_ids) logprobs = [float("nan")] * len(token_ids) for message_or_choice in messages_and_choices: - if isinstance(message_or_choice, dict): - continue - choice = message_or_choice - assert choice.logprobs or allow_training_without_logprobs, ( - "Chat completion choices must have logprobs" - ) - if not choice.logprobs: - continue - token_logprobs = choice.logprobs.content or choice.logprobs.refusal or [] - sentinal_index = token_ids.index(sentinal_token_id) if ( - bytes(token_logprobs[0].bytes or []).decode("utf-8") - == "" - == tokenizer.decode(token_ids[sentinal_index - 4]) + isinstance(message_or_choice, dict) + and not message_or_choice["role"] == "assistant" ): - start = sentinal_index - 4 + continue + start = token_ids.index(sentinal_start_token_id) + end = token_ids.index(sentinal_end_token_id) + 1 + if isinstance(message_or_choice, dict): + token_ids[start:end] = token_ids[start + 1 : end - 1] + logprobs[start:end] = [float("nan")] * (end - start - 2) + assistant_mask[start:end] = [1] * (end - start - 2) else: - start = sentinal_index - end = sentinal_index + 1 - token_ids[start:end] = ( - int(token_logprob.token.split(":")[1]) for token_logprob in token_logprobs - ) - logprobs[start:end] = ( - token_logprob.logprob for token_logprob in token_logprobs - ) - assistant_mask[start:end] = [1] * len(token_logprobs) + choice = message_or_choice + assert choice.logprobs or allow_training_without_logprobs, ( + "Chat completion choices must have logprobs" + ) + if not choice.logprobs: + continue + token_logprobs = choice.logprobs.content or choice.logprobs.refusal or [] + if ( + bytes(token_logprobs[0].bytes or []).decode("utf-8") + == "" + == tokenizer.decode(token_ids[start - 4]) + ): + start -= 4 + token_ids[start:end] = ( + int(token_logprob.token.split(":")[1]) + for token_logprob in token_logprobs + ) + logprobs[start:end] = ( + token_logprob.logprob for token_logprob in token_logprobs + ) + assistant_mask[start:end] = [1] * len(token_logprobs) return TokenizedResult( advantage=advantage, chat=chat, diff --git a/src/art/torchtune/batch.py b/src/art/torchtune/batch.py index 337a669d..b084b9fc 100644 --- a/src/art/torchtune/batch.py +++ b/src/art/torchtune/batch.py @@ -1,7 +1,7 @@ from pydantic import BaseModel from .. import dev, types -from ..local.pack import DiskPackedTensors +from ..preprocessing.pack import DiskPackedTensors class Batch(BaseModel): diff --git a/src/art/torchtune/recipe.py b/src/art/torchtune/recipe.py index 48677cea..afaaec3d 100644 --- a/src/art/torchtune/recipe.py +++ b/src/art/torchtune/recipe.py @@ -47,7 +47,7 @@ from tqdm import tqdm from .. import dev, types -from ..local.pack import PackedTensors, packed_tensors_from_dir +from ..preprocessing.pack import PackedTensors, packed_tensors_from_dir from .batch import Batch from .config import ( CompileConfig, diff --git a/src/art/torchtune/service.py b/src/art/torchtune/service.py index 4abbd0d2..a22f954a 100644 --- a/src/art/torchtune/service.py +++ b/src/art/torchtune/service.py @@ -16,7 +16,7 @@ from vllm.v1.engine.async_llm import AsyncLLM from .. import dev, types -from ..local.pack import DiskPackedTensors +from ..preprocessing.pack import DiskPackedTensors from ..vllm import get_llm, get_worker, openai_server_task, run_on_workers from .batch import Batch diff --git a/src/art/unsloth/decoupled_service.py b/src/art/unsloth/decoupled_service.py index 6fa42c28..428fbfb1 100644 --- a/src/art/unsloth/decoupled_service.py +++ b/src/art/unsloth/decoupled_service.py @@ -22,7 +22,11 @@ from .. import dev, types from ..local.checkpoints import get_last_checkpoint_dir -from ..local.pack import DiskPackedTensors, PackedTensors, packed_tensors_from_dir +from ..preprocessing.pack import ( + DiskPackedTensors, + PackedTensors, + packed_tensors_from_dir, +) from ..utils.get_model_step import get_step_from_dir from ..utils.output_dirs import get_step_checkpoint_dir from ..vllm import get_llm, get_worker, openai_server_task, run_on_workers diff --git a/src/art/unsloth/service.py b/src/art/unsloth/service.py index efc04dcf..b47b8cfb 100644 --- a/src/art/unsloth/service.py +++ b/src/art/unsloth/service.py @@ -10,7 +10,11 @@ from .. import dev, types from ..local.checkpoints import get_last_checkpoint_dir -from ..local.pack import DiskPackedTensors, PackedTensors, packed_tensors_from_dir +from ..preprocessing.pack import ( + DiskPackedTensors, + PackedTensors, + packed_tensors_from_dir, +) from .train import train if TYPE_CHECKING: diff --git a/tests/unit/test_tokenize_trajectory_groups.ipynb b/tests/unit/test_tokenize_trajectory_groups.ipynb new file mode 100644 index 00000000..ff715dba --- /dev/null +++ b/tests/unit/test_tokenize_trajectory_groups.ipynb @@ -0,0 +1,111 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "93a238e4", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "84717d3b", + "metadata": {}, + "outputs": [], + "source": [ + "from IPython.display import clear_output\n", + "from openai.types.chat.chat_completion import Choice, ChoiceLogprobs\n", + "from openai.types.chat.chat_completion_message import ChatCompletionMessage\n", + "from openai.types.chat.chat_completion_token_logprob import ChatCompletionTokenLogprob\n", + "from transformers import AutoTokenizer\n", + "\n", + "import art\n", + "from art.preprocessing.tokenize import tokenize_trajectory_groups\n", + "\n", + "tokenizer = AutoTokenizer.from_pretrained(\"Qwen/Qwen2.5-7B-Instruct\")\n", + "clear_output()\n", + "\n", + "tokenized_results = list(\n", + " tokenize_trajectory_groups(\n", + " tokenizer,\n", + " [\n", + " art.TrajectoryGroup(\n", + " [\n", + " art.Trajectory(\n", + " messages_and_choices=[\n", + " {\n", + " \"role\": \"user\",\n", + " \"content\": \"What is the capital of France?\",\n", + " },\n", + " {\"role\": \"assistant\", \"content\": \"London\"},\n", + " ],\n", + " reward=0.0,\n", + " ),\n", + " art.Trajectory(\n", + " messages_and_choices=[\n", + " {\n", + " \"role\": \"user\",\n", + " \"content\": \"What is the capital of France?\",\n", + " },\n", + " Choice(\n", + " finish_reason=\"stop\",\n", + " index=0,\n", + " logprobs=ChoiceLogprobs(\n", + " content=[\n", + " ChatCompletionTokenLogprob(\n", + " token=\"token:59604\",\n", + " bytes=[80, 97, 114, 105, 115],\n", + " logprob=-0.01,\n", + " top_logprobs=[],\n", + " )\n", + " ]\n", + " ),\n", + " message=ChatCompletionMessage(\n", + " content=\"Paris\",\n", + " role=\"assistant\",\n", + " ),\n", + " ),\n", + " ],\n", + " reward=1.0,\n", + " ),\n", + " ]\n", + " )\n", + " ],\n", + " allow_training_without_logprobs=True,\n", + " scale_rewards=True,\n", + " )\n", + ")\n", + "for result in tokenized_results:\n", + " # set prompt_id to 0 to eliminate stochasticity\n", + " result.prompt_id = 0\n", + " display(result)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.13" + } + }, + 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