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Revert "Update transformers tests generation util v4.45.2 (#1441)" #1614

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Dec 16, 2024
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Revert "Update transformers tests generation util v4.45.2 (#1441)" #1614

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141 changes: 0 additions & 141 deletions conftest.py
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Original file line number Diff line number Diff line change
@@ -1,88 +1,3 @@
# coding=utf-8
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest
import pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser


NOT_DEVICE_TESTS = {
"test_tokenization",
"test_processor",
"test_processing",
"test_beam_constraints",
"test_configuration_utils",
"test_data_collator",
"test_trainer_callback",
"test_trainer_utils",
"test_feature_extraction",
"test_image_processing",
"test_image_processor",
"test_image_transforms",
"test_optimization",
"test_retrieval",
"test_config",
"test_from_pretrained_no_checkpoint",
"test_keep_in_fp32_modules",
"test_gradient_checkpointing_backward_compatibility",
"test_gradient_checkpointing_enable_disable",
"test_save_load_fast_init_from_base",
"test_fast_init_context_manager",
"test_fast_init_tied_embeddings",
"test_save_load_fast_init_to_base",
"test_torch_save_load",
"test_initialization",
"test_forward_signature",
"test_model_get_set_embeddings",
"test_model_main_input_name",
"test_correct_missing_keys",
"test_tie_model_weights",
"test_can_use_safetensors",
"test_load_save_without_tied_weights",
"test_tied_weights_keys",
"test_model_weights_reload_no_missing_tied_weights",
"test_pt_tf_model_equivalence",
"test_mismatched_shapes_have_properly_initialized_weights",
"test_matched_shapes_have_loaded_weights_when_some_mismatched_shapes_exist",
"test_model_is_small",
"test_tf_from_pt_safetensors",
"test_flax_from_pt_safetensors",
"ModelTest::test_pipeline_", # None of the pipeline tests from PipelineTesterMixin (of which XxxModelTest inherits from) are running on device
"ModelTester::test_pipeline_",
"/repo_utils/",
"/utils/",
"/agents/",
}

# allow having multiple repository checkouts and not needing to remember to rerun
# `pip install -e '.[dev]'` when switching between checkouts and running tests.
git_repo_path = abspath(join(dirname(__file__), "src"))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action="ignore", category=FutureWarning)


class Secret:
"""
Taken from: https://stackoverflow.com/a/67393351
Expand All @@ -98,69 +13,13 @@ def __str___(self):
return "*******"


def pytest_configure(config):
config.addinivalue_line(
"markers", "is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested"
)
config.addinivalue_line(
"markers", "is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested"
)
config.addinivalue_line("markers", "is_pipeline_test: mark test to run only when pipelines are tested")
config.addinivalue_line("markers", "is_staging_test: mark test to run only in the staging environment")
config.addinivalue_line("markers", "accelerate_tests: mark test that require accelerate")
config.addinivalue_line("markers", "agent_tests: mark the agent tests that are run on their specific schedule")
config.addinivalue_line("markers", "not_device_test: mark the tests always running on cpu")


def pytest_collection_modifyitems(items):
for item in items:
if any(test_name in item.nodeid for test_name in NOT_DEVICE_TESTS):
item.add_marker(pytest.mark.not_device_test)


def pytest_addoption(parser):
parser.addoption("--token", action="store", default=None)

from transformers.testing_utils import pytest_addoption_shared

pytest_addoption_shared(parser)


def pytest_terminal_summary(terminalreporter):
from transformers.testing_utils import pytest_terminal_summary_main

make_reports = terminalreporter.config.getoption("--make-reports")
if make_reports:
pytest_terminal_summary_main(terminalreporter, id=make_reports)


def pytest_sessionfinish(session, exitstatus):
# If no tests are collected, pytest exists with code 5, which makes the CI fail.
if exitstatus == 5:
session.exitstatus = 0


def pytest_generate_tests(metafunc):
# This is called for every test. Only get/set command line arguments
# if the argument is specified in the list of test "fixturenames".
option_value = Secret(metafunc.config.option.token)
if "token" in metafunc.fixturenames:
metafunc.parametrize("token", [option_value])


# Doctest custom flag to ignore output.
IGNORE_RESULT = doctest.register_optionflag("IGNORE_RESULT")

OutputChecker = doctest.OutputChecker


class CustomOutputChecker(OutputChecker):
def check_output(self, want, got, optionflags):
if IGNORE_RESULT & optionflags:
return True
return OutputChecker.check_output(self, want, got, optionflags)


doctest.OutputChecker = CustomOutputChecker
_pytest.doctest.DoctestModule = HfDoctestModule
doctest.DocTestParser = HfDocTestParser
29 changes: 12 additions & 17 deletions optimum/habana/transformers/generation/utils.py
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Expand Up @@ -211,20 +211,19 @@ def _prepare_decoder_input_ids_for_generation(
# 2. `decoder_start_token_id` must have shape (batch_size, 1)
if device is None:
device = self.device
if decoder_start_token_id.ndim == 1:
if decoder_start_token_id.shape[0] != batch_size:
raise ValueError(
f"`decoder_start_token_id` expected to have length {batch_size} but got {decoder_start_token_id.shape[0]}"
if token_idx is None:
if decoder_start_token_id.ndim == 1:
if decoder_start_token_id.shape[0] != batch_size:
raise ValueError(
f"`decoder_start_token_id` expected to have length {batch_size} but got {decoder_start_token_id.shape[0]}"
)
decoder_start_token_id = decoder_start_token_id.view(-1, 1)
else:
decoder_start_token_id = (
torch.ones((batch_size, 1), dtype=torch.long, device=device) * decoder_start_token_id
)
decoder_start_token_id = decoder_start_token_id.view(-1, 1)
else:
decoder_start_token_id = (
torch.ones((batch_size, 1), dtype=torch.long, device=device) * decoder_start_token_id
)

if token_idx is not None:
# creating padded decoder_input_ids to achieve static shapes.
# Later new tokens once generated are copied in to decoder_input_ids based on token_idx
# creating padded decoder_input_ids to achieve static shapes. Later new tokens once generated are copied in to decoder_input_ids based on token_idx
max_length = max_new_tokens + 1 if max_new_tokens is not None else self.generation_config.max_length
decoder_start_token_id = (
torch.ones((batch_size, 1), dtype=torch.long, device=device) * decoder_start_token_id
Expand Down Expand Up @@ -3040,8 +3039,7 @@ def expand_if_needed(tensor, new_size, value, dim=-1):
if self.generation_config.early_stopping:
num_eos_tokens.add_(beam_tokens[0:num_beams].eq(self.config.eos_token_id).sum())

if self.config.eos_token_id is not None:
beam_scores.add_(torch.where(beam_tokens.eq(self.config.eos_token_id), float("-inf"), 0.0))
beam_scores.add_(torch.where(beam_tokens.eq(self.config.eos_token_id), float("-inf"), 0.0))
beam_scores = beam_scores.view(batch_size, -1).unsqueeze(0)
_, selected = torch.topk(beam_scores, k=num_beams, dim=-1, largest=True, sorted=True)
offset = torch.arange(0, torch.numel(beam_scores), beam_scores.shape[-1]).unsqueeze(-1)
Expand Down Expand Up @@ -3213,9 +3211,6 @@ def move(obj, device):
if not output_scores:
sequence_outputs["sequence_scores"] = None

if self.generation_config.static_shapes:
raise NotImplementedError("sequence_scores is not implemented for static_shapes")

if self.config.is_encoder_decoder:
return GenerateBeamEncoderDecoderOutput(
sequences=sequence_outputs["sequences"],
Expand Down
4 changes: 1 addition & 3 deletions optimum/habana/transformers/models/bart/modeling_bart.py
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Expand Up @@ -458,9 +458,7 @@ def gaudi_BartDecoder_forward(

# past_key_values_length
past_key_values_length = past_key_values[0][0].shape[2] if past_key_values is not None else 0
tensor_past_key_values_length = (
token_idx - 1 if (use_cache and token_idx is not None) else torch.tensor(past_key_values_length)
)
tensor_past_key_values_length = token_idx - 1 if use_cache else torch.tensor(past_key_values_length)

if inputs_embeds is None:
inputs_embeds = self.embed_tokens(input)
Expand Down
9 changes: 0 additions & 9 deletions pyproject.toml
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Expand Up @@ -41,12 +41,3 @@ skip-magic-trailing-comma = false

# Like Black, automatically detect the appropriate line ending.
line-ending = "auto"

[tool.pytest.ini_options]
addopts = "--doctest-glob='**/*.md'"
doctest_optionflags="NUMBER NORMALIZE_WHITESPACE ELLIPSIS"
markers = [
"flash_attn_test: marks tests related to flash attention (deselect with '-m \"not flash_attn_test\"')",
"bitsandbytes: select (or deselect with `not`) bitsandbytes integration tests",
"generate: marks tests that use the GenerationTesterMixin"
]
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