repo_id stringclasses 409
values | prefix large_stringlengths 34 36.3k | target large_stringlengths 1 498 | assertion_type stringclasses 31
values | difficulty stringclasses 8
values | test_file stringlengths 10 121 | test_function stringlengths 1 104 | test_class stringlengths 0 51 | lineno int32 2 11.3k | commit_idx int32 |
|---|---|---|---|---|---|---|---|---|---|
EbodShojaei/bake | from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
from mbake.core.rules import (
AssignmentSpacingRule,
ContinuationRule,
PhonyRule,
TabsRule,
TargetSpacingRule,
WhitespaceRule,
)
class TestContinuationRule:
def test_formats_simple_continua... | "SOURCES = file1.c \\" | assert | string_literal | tests/test_bake.py | test_formats_simple_continuation | TestContinuationRule | 173 | null |
EbodShojaei/bake | from unittest.mock import MagicMock, patch
import pytest
from mbake.utils.version_utils import (
VersionError,
check_for_updates,
get_pypi_version,
is_development_install,
parse_version,
)
class TestCheckForUpdates:
@patch("mbake.utils.version_utils.get_pypi_version")
@patch("mbake.utils... | "1.0.0" | assert | string_literal | tests/test_version_utils.py | test_network_error | TestCheckForUpdates | 154 | null |
EbodShojaei/bake | import tempfile
from pathlib import Path
from unittest.mock import patch
import pytest
from typer.testing import CliRunner
from mbake.cli import app
class TestValidateCommand:
def runner(self):
"""Create a CLI runner for testing."""
return CliRunner()
def test_validate_makefile_with_relativ... | subdir | assert | variable | tests/test_validate_command.py | test_validate_makefile_with_relative_include | TestValidateCommand | 86 | null |
EbodShojaei/bake | from pathlib import Path
from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
from mbake.core.rules.assignment_alignment import AssignmentAlignmentRule
def create_alignment_config(
align_assignments: bool = True, align_across_comments: bool = False
) -> Config:
"... | "LONGER_VAR3 += -more" | assert | string_literal | tests/test_assignment_alignment.py | test_alignment_with_different_operators | TestAssignmentAlignment | 80 | null |
EbodShojaei/bake | from unittest.mock import MagicMock, patch
import pytest
from mbake.utils.version_utils import (
VersionError,
check_for_updates,
get_pypi_version,
is_development_install,
parse_version,
)
class TestCheckForUpdates:
@patch("mbake.utils.version_utils.get_pypi_version")
@patch("mbake.utils... | "1.1.0" | assert | string_literal | tests/test_version_utils.py | test_update_available | TestCheckForUpdates | 117 | null |
EbodShojaei/bake | from pathlib import Path
from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
from mbake.core.rules.assignment_alignment import AssignmentAlignmentRule
def create_alignment_config(
align_assignments: bool = True, align_across_comments: bool = False
) -> Config:
"... | "ifdef DEBUG" | assert | string_literal | tests/test_assignment_alignment.py | test_conditional_blocks_break_alignment | TestAssignmentAlignment | 236 | null |
EbodShojaei/bake | from unittest.mock import MagicMock, patch
import pytest
from mbake.utils.version_utils import (
VersionError,
check_for_updates,
get_pypi_version,
is_development_install,
parse_version,
)
class TestCheckForUpdates:
@patch("mbake.utils.version_utils.get_pypi_version")
@patch("mbake.utils... | False | assert | bool_literal | tests/test_version_utils.py | test_network_error | TestCheckForUpdates | 152 | null |
EbodShojaei/bake | from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
class TestReversedAssignmentOperators:
def test_mixed_correct_and_incorrect_operators(self):
"""Test mix of correct and incorrect operators."""
config = Config(formatter=FormatterConfig())
f... | [7, 8, 9] | assert | collection | tests/test_reversed_assignment_operators.py | test_mixed_correct_and_incorrect_operators | TestReversedAssignmentOperators | 276 | null |
EbodShojaei/bake | from pathlib import Path
from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
from mbake.core.rules.assignment_alignment import AssignmentAlignmentRule
def create_alignment_config(
align_assignments: bool = True, align_across_comments: bool = False
) -> Config:
"... | "AFTER = test" | assert | string_literal | tests/test_assignment_alignment.py | test_comments_break_blocks | TestAssignmentAlignment | 106 | null |
EbodShojaei/bake | from pathlib import Path
from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
from mbake.core.rules.assignment_alignment import AssignmentAlignmentRule
def create_alignment_config(
align_assignments: bool = True, align_across_comments: bool = False
) -> Config:
"... | "VAR1 = value1" | assert | string_literal | tests/test_assignment_alignment.py | test_conditional_blocks_break_alignment | TestAssignmentAlignment | 233 | null |
EbodShojaei/bake | from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
from mbake.core.rules import (
AssignmentSpacingRule,
ContinuationRule,
PhonyRule,
TabsRule,
TargetSpacingRule,
WhitespaceRule,
)
class TestTabsRule:
def test_handles_mixed_indentation(self)... | ["target:", "\techo 'mixed'"] | assert | collection | tests/test_bake.py | test_handles_mixed_indentation | TestTabsRule | 51 | null |
EbodShojaei/bake | from mbake.config import Config, FormatterConfig
from mbake.core.formatter import MakefileFormatter
from mbake.core.rules import (
AssignmentSpacingRule,
ContinuationRule,
PhonyRule,
TabsRule,
TargetSpacingRule,
WhitespaceRule,
)
class TestFinalNewlineRule:
def test_detects_missing_final_n... | 1 | assert | numeric_literal | tests/test_bake.py | test_detects_missing_final_newline | TestFinalNewlineRule | 129 | null |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | 5 | assert | numeric_literal | ultravox/data/datasets_test.py | test_range | 157 | null | |
fixie-ai/ultravox | import pytest
import transformers
from ultravox.model import ultravox_config
@pytest.mark.parametrize(
"model_id",
["fixie-ai/ultravox-v0_2", "fixie-ai/ultravox-v0_3", "fixie-ai/ultravox-v0_4"],
)
def test_can_load_release(model_id: str):
orig_config: transformers.PretrainedConfig = (
transformers... | orig_config.text_config.to_dict() | assert | func_call | ultravox/model/ultravox_config_test.py | test_can_load_release | 33 | null | |
fixie-ai/ultravox | import re
from unittest import mock
from ultravox.evaluation import eval_types
from ultravox.evaluation import gpt_eval
from ultravox.evaluation import gpt_eval_conv
def test_evaluate_conversation():
gpt_eval.gpt_evaluator.client = mock.MagicMock()
sample = eval_types.Sample(
index=0,
history=... | 2 | assert | numeric_literal | ultravox/evaluation/gpt_eval_test.py | test_evaluate_conversation | 28 | null | |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | 2 | assert | numeric_literal | ultravox/data/datasets_test.py | test_dataset_config_serialization | 236 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [1, 1] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_multiple_audios | 110 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | 1 | assert | numeric_literal | ultravox/model/ultravox_model_test.py | test_init_latency_mask_valid | 36 | null | |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | 1000 | assert | numeric_literal | ultravox/data/datasets_test.py | test_dataset_config | 211 | null | |
fixie-ai/ultravox | import os
from typing import Optional
from unittest import mock
import numpy as np
import pytest
import torch
import transformers
from ultravox import data as datasets
from ultravox.inference import base as infer_base
from ultravox.inference import infer
from ultravox.model import ultravox_processing
def tokenizer()... | None | assert | none_literal | ultravox/inference/infer_test.py | test_infer_text_only | 174 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [100, 1000] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_multiple_audios | 99 | null | |
fixie-ai/ultravox | import torch
import torch.nn as nn
from ultravox.tools import projector_combine_tool
def test_combine_linear_layers():
linear_1 = nn.Linear(10, 12, bias=False)
linear_2 = nn.Linear(12, 23, bias=False)
combined = projector_combine_tool.combine_linear_layers(linear_1, linear_2)
test_inp = torch.randn(1,... | linear_1.in_features | assert | complex_expr | ultravox/tools/projector_combine_tool_test.py | test_combine_linear_layers | 12 | null | |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | 5000 | assert | numeric_literal | ultravox/data/datasets_test.py | test_dataset_config | 205 | null | |
fixie-ai/ultravox | import pytest
import transformers
from ultravox.model import ultravox_config
@pytest.mark.parametrize(
"model_id",
["fixie-ai/ultravox-v0_2", "fixie-ai/ultravox-v0_3", "fixie-ai/ultravox-v0_4"],
)
def test_can_load_release(model_id: str):
orig_config: transformers.PretrainedConfig = (
transformers... | orig_values | assert | variable | ultravox/model/ultravox_config_test.py | test_can_load_release | 30 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | 100, rel=1e-2) | pytest.approx | complex_expr | ultravox/evaluation/string_metrics_test.py | test_wer_en_cap_hypothesis_len | 78 | null | |
fixie-ai/ultravox | import re
from unittest import mock
from ultravox.evaluation import eval_types
from ultravox.evaluation import gpt_eval
from ultravox.evaluation import gpt_eval_conv
def test_evaluate_conversation():
gpt_eval.gpt_evaluator.client = mock.MagicMock()
sample = eval_types.Sample(
index=0,
history=... | gpt_question | assert | variable | ultravox/evaluation/gpt_eval_test.py | test_evaluate_conversation | 32 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [1, 2, 1] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_multiple_audios_with_overflowing_audio | 137 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | expected_output | assert | variable | ultravox/evaluation/string_metrics_test.py | test_remove_diacritics | 127 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [7, 63] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_multiple_audios | 100 | null | |
fixie-ai/ultravox | import os
from typing import Optional
from unittest import mock
import numpy as np
import pytest
import torch
import transformers
from ultravox import data as datasets
from ultravox.inference import base as infer_base
from ultravox.inference import infer
from ultravox.model import ultravox_processing
def tokenizer()... | 20 | assert | numeric_literal | ultravox/inference/infer_test.py | test_infer_16kHz | 97 | null | |
fixie-ai/ultravox | import os
from typing import Optional
from unittest import mock
import numpy as np
import pytest
import torch
import transformers
from ultravox import data as datasets
from ultravox.inference import base as infer_base
from ultravox.inference import infer
from ultravox.model import ultravox_processing
def tokenizer()... | 12 | assert | numeric_literal | ultravox/inference/infer_test.py | test_infer_text_only | 170 | null | |
fixie-ai/ultravox | import re
from unittest import mock
from ultravox.evaluation import eval_types
from ultravox.evaluation import gpt_eval
from ultravox.evaluation import gpt_eval_conv
def test_evaluate_conversation():
gpt_eval.gpt_evaluator.client = mock.MagicMock()
sample = eval_types.Sample(
index=0,
history=... | "user" | assert | string_literal | ultravox/evaluation/gpt_eval_test.py | test_evaluate_conversation | 30 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | model.state_dict()) | assert_* | func_call | ultravox/model/ultravox_model_test.py | test_load_pretrained_model | 111 | null | |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | 90 | assert | numeric_literal | ultravox/data/datasets_test.py | test_generic_dataset_multiple_splits | 399 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [3, 12] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_multiple_audios | 101 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | 61.216343280457046, rel=1e-2) | pytest.approx | complex_expr | ultravox/evaluation/string_metrics_test.py | test_bleu_en | 101 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | 4 | assert | numeric_literal | ultravox/model/ultravox_model_test.py | test_init_latency_mask_valid | 35 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [2] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_overflowing_audio | 88 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | 9.090909090909092, rel=1e-2) | pytest.approx | complex_expr | ultravox/evaluation/string_metrics_test.py | test_wer_en | 71 | null | |
fixie-ai/ultravox | import json
import jinja2
def test_quotes():
with open("tools/ds_tool/soda_alt_last_turn.jinja", "r") as template_file:
template = template_file.read()
dialogue = [
'Have you ever used a double quote (")',
"Of course, what about a single quote (')?",
'"Yes, I have."',
... | 4 | assert | numeric_literal | ultravox/tools/ds_tool/template_test.py | test_quotes | 24 | null | |
fixie-ai/ultravox | from typing import Union
import numpy as np
import pytest
from ultravox.data import data_sample
def _create_sine_wave(
freq: int = 440,
duration: float = 1.0,
sample_rate: int = 16000,
amplitude: float = 0.1,
target_dtype: str = "float32",
) -> Union[
np.typing.NDArray[np.float32],
np.typ... | AssertionError) | pytest.raises | variable | ultravox/data/data_sample_test.py | test_create_sample__raises_on_unsupported_dtype | 80 | null | |
fixie-ai/ultravox | import json
import jinja2
def test_quotes():
with open("tools/ds_tool/soda_alt_last_turn.jinja", "r") as template_file:
template = template_file.read()
dialogue = [
'Have you ever used a double quote (")',
"Of course, what about a single quote (')?",
'"Yes, I have."',
... | "user" | assert | string_literal | ultravox/tools/ds_tool/template_test.py | test_quotes | 22 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | None | assert | none_literal | ultravox/model/ultravox_model_test.py | test_init_latency_mask_none | 27 | null | |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | 4 | assert | numeric_literal | ultravox/data/datasets_test.py | test_dataset_config | 203 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | encoder._buffers | assert | complex_expr | ultravox/model/ultravox_model_test.py | test_init_latency_mask_persistence | 68 | null | |
fixie-ai/ultravox | import json
import jinja2
def test_quotes():
with open("tools/ds_tool/soda_alt_last_turn.jinja", "r") as template_file:
template = template_file.read()
dialogue = [
'Have you ever used a double quote (")',
"Of course, what about a single quote (')?",
'"Yes, I have."',
... | "system" | assert | string_literal | ultravox/tools/ds_tool/template_test.py | test_quotes | 25 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | 15.384615384615385, rel=1e-2) | pytest.approx | complex_expr | ultravox/evaluation/string_metrics_test.py | test_wer_zh | 91 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [1] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_single_audio | 58 | null | |
fixie-ai/ultravox | from typing import Union
import numpy as np
import pytest
from ultravox.data import data_sample
def _create_sine_wave(
freq: int = 440,
duration: float = 1.0,
sample_rate: int = 16000,
amplitude: float = 0.1,
target_dtype: str = "float32",
) -> Union[
np.typing.NDArray[np.float32],
np.typ... | None | assert | none_literal | ultravox/data/data_sample_test.py | _create_and_validate_sample | 46 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | 45.43741956108463, rel=1e-2) | pytest.approx | complex_expr | ultravox/evaluation/string_metrics_test.py | test_bleu_zh | 106 | null | |
fixie-ai/ultravox | import pytest
import transformers
from ultravox.model import ultravox_config
def test_no_config_when_id_present():
config = ultravox_config.UltravoxConfig(audio_model_id="openai/whisper-small")
assert "audio_config" not in | config.to_diff_dict() | assert | func_call | ultravox/model/ultravox_config_test.py | test_no_config_when_id_present | 44 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [188, 32] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_overflowing_audio | 82 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | torch.finfo(dtype).min | assert | func_call | ultravox/model/ultravox_model_test.py | test_init_latency_mask_different_dtypes | 62 | null | |
fixie-ai/ultravox | import torch
import torch.nn as nn
from ultravox.tools import projector_combine_tool
def test_combine_linear_layers():
linear_1 = nn.Linear(10, 12, bias=False)
linear_2 = nn.Linear(12, 23, bias=False)
combined = projector_combine_tool.combine_linear_layers(linear_1, linear_2)
test_inp = torch.randn(1,... | linear_2.out_features | assert | complex_expr | ultravox/tools/projector_combine_tool_test.py | test_combine_linear_layers | 13 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [4] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_multiple_audios_with_overflowing_audio | 136 | null | |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | 10 | assert | numeric_literal | ultravox/data/datasets_test.py | test_range | 164 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [3, 3] | assert | collection | ultravox/model/ultravox_processing_test.py | test_collator_with_audio | 209 | null | |
fixie-ai/ultravox | import platform
import numpy as np
import pytest
from ultravox.data.aug import AugRegistry
@pytest.mark.parametrize("gain_db", [10, -10])
def test_gain(gain_db):
augmentation_config = AugRegistry.get_config("gain", {"gain_db": gain_db})
augmentation = AugRegistry.create_augmentation(augmentation_config)
... | audio.shape | assert | complex_expr | ultravox/data/aug/test_augs.py | test_gain | 15 | null | |
fixie-ai/ultravox | from unittest import mock
import numpy as np
import pytest
import torch
from ultravox import data as datasets
from ultravox.model import ultravox_config
from ultravox.model import ultravox_data_proc
TEST_USER_MESSAGE = {
"role": "user",
"content": "Listen to <|audio|> and respond.",
}
TEST_ASSISTANT_MESSAGE ... | torch.Size([1, 1, 3]) | assert | func_call | ultravox/model/ultravox_data_proc_test.py | test_process | 88 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | ValueError) | pytest.raises | variable | ultravox/model/ultravox_processing_test.py | test_processor_fails_with_too_many_audio_tokens | 143 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | AssertionError, match="must divide .* evenly") | pytest.raises | complex_expr | ultravox/model/ultravox_model_test.py | test_init_latency_mask_invalid_block_size | 54 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | pytest.approx(15.384615384615385, rel=1e-2) | assert | func_call | ultravox/evaluation/string_metrics_test.py | test_wer_zh | 91 | null | |
fixie-ai/ultravox | from typing import Optional
from unittest.mock import patch
import datasets as hf_datasets
import numpy as np
import pytest
import torch
from torch.utils import data
from transformers.feature_extraction_utils import BatchFeature
from ultravox.data import data_sample
from ultravox.data import datasets
from ultravox.da... | "0" | assert | string_literal | ultravox/data/datasets_test.py | test_transcribe_dataset | 179 | null | |
fixie-ai/ultravox | import os
from typing import Optional
from unittest import mock
import numpy as np
import pytest
import torch
import transformers
from ultravox import data as datasets
from ultravox.inference import base as infer_base
from ultravox.inference import infer
from ultravox.model import ultravox_processing
def tokenizer()... | "56789" | assert | string_literal | ultravox/inference/infer_test.py | test_infer_16kHz | 99 | null | |
fixie-ai/ultravox | import os
import pytest
import safetensors.torch
import torch
import transformers
from ultravox.model import ultravox_config
from ultravox.model import ultravox_model
TINY_MODEL_PATH = "./assets/tiny_ultravox"
def encoder():
config = transformers.WhisperConfig(
max_source_positions=1500,
d_model... | dict_b[k]) | assert_* | complex_expr | ultravox/model/ultravox_model_test.py | assert_equal_state_dict | 74 | null | |
fixie-ai/ultravox | from typing import Union
import numpy as np
import pytest
from ultravox.data import data_sample
def _create_sine_wave(
freq: int = 440,
duration: float = 1.0,
sample_rate: int = 16000,
amplitude: float = 0.1,
target_dtype: str = "float32",
) -> Union[
np.typing.NDArray[np.float32],
np.typ... | np.float32 | assert | complex_expr | ultravox/data/data_sample_test.py | _create_and_validate_sample | 48 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | pytest.approx(45.43741956108463, rel=1e-2) | assert | func_call | ultravox/evaluation/string_metrics_test.py | test_bleu_zh | 106 | null | |
fixie-ai/ultravox | import json
import jinja2
def test_quotes():
with open("tools/ds_tool/soda_alt_last_turn.jinja", "r") as template_file:
template = template_file.read()
dialogue = [
'Have you ever used a double quote (")',
"Of course, what about a single quote (')?",
'"Yes, I have."',
... | dialogue[:-1] | assert | complex_expr | ultravox/tools/ds_tool/template_test.py | test_quotes | 26 | null | |
fixie-ai/ultravox | import platform
import numpy as np
import pytest
from ultravox.data.aug import AugRegistry
def test_all_registered_augmentations():
"""
Test that all registered augmentations can be created and applied to audio data.
This ensures that every augmentation in the registry is working as expected.
"""
... | 0 | assert | numeric_literal | ultravox/data/aug/test_augs.py | test_all_registered_augmentations | 57 | null | |
fixie-ai/ultravox | import os
import pytest
import torch.distributed
from torch import multiprocessing as mp
from ultravox.training import ddp_utils
os.environ["MASTER_ADDR"] = "localhost"
os.environ["MASTER_PORT"] = "12355"
def verify_all_gather(rank: int, world_size: int, k: int = 4):
if world_size > 1:
torch.distributed... | list(range(world_size * k)) | assert | func_call | ultravox/training/ddp_utils_test.py | verify_all_gather | 27 | null | |
fixie-ai/ultravox | from typing import Union
import numpy as np
import pytest
from ultravox.data import data_sample
def _create_sine_wave(
freq: int = 440,
duration: float = 1.0,
sample_rate: int = 16000,
amplitude: float = 0.1,
target_dtype: str = "float32",
) -> Union[
np.typing.NDArray[np.float32],
np.typ... | 16000 | assert | numeric_literal | ultravox/data/data_sample_test.py | _create_and_validate_sample | 45 | null | |
fixie-ai/ultravox | import re
from unittest import mock
from ultravox.evaluation import eval_types
from ultravox.evaluation import gpt_eval
from ultravox.evaluation import gpt_eval_conv
def test_evaluate_conversation():
gpt_eval.gpt_evaluator.client = mock.MagicMock()
sample = eval_types.Sample(
index=0,
history=... | "system" | assert | string_literal | ultravox/evaluation/gpt_eval_test.py | test_evaluate_conversation | 29 | null | |
fixie-ai/ultravox | import numpy as np
import pytest
import transformers
from ultravox.model import ultravox_processing
def processor():
audio_processor = transformers.AutoProcessor.from_pretrained(
"./assets/hf/openai-whisper-tiny", local_files_only=True
)
tokenizer = transformers.AutoTokenizer.from_pretrained(
... | [7] | assert | collection | ultravox/model/ultravox_processing_test.py | test_processor_single_audio | 54 | null | |
fixie-ai/ultravox | import os
from typing import Optional
from unittest import mock
import numpy as np
import pytest
import torch
import transformers
from ultravox import data as datasets
from ultravox.inference import base as infer_base
from ultravox.inference import infer
from ultravox.model import ultravox_processing
def tokenizer()... | 7 | assert | numeric_literal | ultravox/inference/infer_test.py | test_infer_16kHz | 108 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | pytest.approx(40.909090909090914, rel=1e-2) | assert | func_call | ultravox/evaluation/string_metrics_test.py | test_wer_ja | 96 | null | |
fixie-ai/ultravox | import pytest
from ultravox.data import text_proc
def test_format_message_history():
roles = {"user": "user", "assistant": "assistant"}
messages = {"role": ["user", "assistant"], "content": ["A", "B"]}
assert text_proc.format_message_history(messages, roles) == | [ {"role": "user", "content": "A"}, {"role": "assistant", "content": "B"}, ] | assert | collection | ultravox/data/text_proc_test.py | test_format_message_history | 28 | null | |
fixie-ai/ultravox | import pytest
from ultravox.data import text_proc
def test_garbage_utterance():
with pytest.raises( | text_proc.FormatASRError) | pytest.raises | complex_expr | ultravox/data/text_proc_test.py | test_garbage_utterance | 20 | null | |
fixie-ai/ultravox | import os
from typing import Optional
from unittest import mock
import numpy as np
import pytest
import torch
import transformers
from ultravox import data as datasets
from ultravox.inference import base as infer_base
from ultravox.inference import infer
from ultravox.model import ultravox_processing
def tokenizer()... | 5 | assert | numeric_literal | ultravox/inference/infer_test.py | test_long_audio_context | 81 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | 350, rel=1e-2) | pytest.approx | complex_expr | ultravox/evaluation/string_metrics_test.py | test_wer_en_cap_hypothesis_len | 83 | null | |
fixie-ai/ultravox | import pytest
from ultravox.evaluation import eval_types
from ultravox.evaluation import string_metrics
samples_en = [
eval_types.Sample(
index=0,
question="",
transcript="",
expected_answer="The quick brown fox jumps over the lazy dog",
generated_answer="The quick brown fo... | pytest.approx(61.216343280457046, rel=1e-2) | assert | func_call | ultravox/evaluation/string_metrics_test.py | test_bleu_en | 101 | null | |
run-llama/llama_deploy | from typing import Any
from unittest import mock
import httpx
from fastapi.testclient import TestClient
from llama_deploy.apiserver.settings import settings
def test_prom_proxy(http_client: TestClient) -> None:
mock_metrics_response = 'metric1{label="value"} 1.0\nmetric2{label="value"} 2.0'
mock_response = h... | mock_metrics_response | assert | variable | tests/apiserver/routers/test_status.py | test_prom_proxy | 35 | null | |
run-llama/llama_deploy | from unittest import mock
from click.testing import CliRunner
from llama_deploy.cli import llamactl
from llama_deploy.types.apiserver import Status, StatusEnum
def test_status(runner: CliRunner) -> None:
with mock.patch("llama_deploy.cli.status.Client") as mocked_client:
mocked_client.return_value.sync.a... | "LlamaDeploy is up and running.\n\nCurrently there are no active deployments\n" | assert | string_literal | tests/cli/test_status.py | test_status | 44 | null | |
run-llama/llama_deploy | import os
from pathlib import Path
from unittest.mock import MagicMock, mock_open, patch
import pytest
from click.testing import CliRunner
from tenacity import RetryError
from llama_deploy.apiserver.settings import settings
from llama_deploy.cli.serve import serve
def runner() -> CliRunner:
"""Fixture for invoki... | mock_file_open.return_value | assert | complex_expr | tests/cli/test_serve.py | test_serve_with_deployment_file | 124 | null | |
run-llama/llama_deploy | from typing import Any
from unittest import mock
import httpx
from fastapi.testclient import TestClient
from llama_deploy.apiserver.settings import settings
def test_read_main(http_client: TestClient) -> None:
response = http_client.get("/status")
assert response.status_code == 200
assert response.json(... | { "max_deployments": 10, "deployments": [], "status": "Healthy", "status_message": "", } | assert | collection | tests/apiserver/routers/test_status.py | test_read_main | 13 | null | |
run-llama/llama_deploy | from unittest import mock
import pytest
from llama_deploy.client import Client
from llama_deploy.client.client import _SyncClient
from llama_deploy.client.models import ApiServer
def test_client_init_default() -> None:
c = Client()
assert c.api_server_url == | "http://localhost:4501" | assert | string_literal | tests/client/test_client.py | test_client_init_default | 12 | null | |
run-llama/llama_deploy | import asyncio
from typing import AsyncGenerator
import pytest
from llama_deploy.client import Client
from llama_deploy.client.models import Collection, Model
from llama_deploy.client.models.model import _async_gen_to_list, make_sync
def test_collection_get() -> None:
class MyCollection(Collection):
pass... | "bar" | assert | string_literal | tests/client/models/test_model.py | test_collection_get | 51 | null | |
run-llama/llama_deploy | from pathlib import Path
from unittest import mock
import pytest
from llama_deploy.apiserver.deployment_config_parser import DeploymentConfig
from llama_deploy.apiserver.source_managers.git import GitSourceManager
def config(data_path: Path) -> DeploymentConfig:
return DeploymentConfig.from_yaml(data_path / "git... | ( "https://example.com/llama_deploy.git", None, ) | assert | collection | tests/apiserver/source_managers/test_git.py | test_parse_source | 21 | null | |
run-llama/llama_deploy | import io
from typing import Any
from unittest import mock
import httpx
import pytest
from llama_deploy.client.models.apiserver import (
ApiServer,
Deployment,
DeploymentCollection,
SessionCollection,
Task,
TaskCollection,
)
from llama_deploy.types import SessionDefinition, TaskDefinition, Tas... | "http://localhost:4501/deployments/a_deployment") | assert_* | string_literal | tests/client/models/test_apiserver.py | test_task_deployment_collection_get | 235 | null | |
run-llama/llama_deploy | from pathlib import Path
import pytest
from llama_deploy.types import TaskDefinition
@pytest.mark.asyncio
async def test_reload(apiserver, client):
here = Path(__file__).parent
deployment_fp = here / "deployments" / "deployment_reload1.yml"
with open(deployment_fp) as f:
deployment = await client... | "I have received:bar" | assert | string_literal | e2e_tests/apiserver/test_reload.py | test_reload | 19 | null | |
run-llama/llama_deploy | from unittest import mock
from click.testing import CliRunner
from llama_deploy.cli import llamactl
from llama_deploy.types.apiserver import Status, StatusEnum
def test_status_with_deployments(runner: CliRunner) -> None:
with mock.patch("llama_deploy.cli.status.Client") as mocked_client:
mocked_client.re... | "LlamaDeploy is up and running.\n\nActive deployments:\n- foo\n- bar\n" | assert | string_literal | tests/cli/test_status.py | test_status_with_deployments | 61 | null | |
run-llama/llama_deploy | from typing import Any
from unittest import mock
import httpx
from fastapi.testclient import TestClient
from llama_deploy.apiserver.settings import settings
def test_prom_proxy_off(http_client: TestClient, monkeypatch: Any) -> None:
monkeypatch.setattr(settings, "prometheus_enabled", False)
response = http_c... | 204 | assert | numeric_literal | tests/apiserver/routers/test_status.py | test_prom_proxy_off | 24 | null | |
run-llama/llama_deploy | import io
from typing import Any
from unittest import mock
import httpx
import pytest
from llama_deploy.client.models.apiserver import (
ApiServer,
Deployment,
DeploymentCollection,
SessionCollection,
Task,
TaskCollection,
)
from llama_deploy.types import SessionDefinition, TaskDefinition, Tas... | "Down" | assert | string_literal | tests/client/models/test_apiserver.py | test_status_down | 253 | null | |
run-llama/llama_deploy | from typing import Any
from unittest import mock
import httpx
from fastapi.testclient import TestClient
from llama_deploy.apiserver.settings import settings
def test_prom_proxy_failure(http_client: TestClient) -> None:
# Mock the HTTP client to raise an exception
with mock.patch(
"httpx.AsyncClient.g... | "Connection failed" | assert | string_literal | tests/apiserver/routers/test_status.py | test_prom_proxy_failure | 45 | null | |
run-llama/llama_deploy | import io
from typing import Any
from unittest import mock
import httpx
import pytest
from llama_deploy.client.models.apiserver import (
ApiServer,
Deployment,
DeploymentCollection,
SessionCollection,
Task,
TaskCollection,
)
from llama_deploy.types import SessionDefinition, TaskDefinition, Tas... | 2 | assert | numeric_literal | tests/client/models/test_apiserver.py | test_session_collection_list | 84 | null | |
run-llama/llama_deploy | from unittest import mock
from click.testing import CliRunner
from llama_deploy.cli import llamactl
from llama_deploy.cli.__main__ import main
def test_root_command(runner: CliRunner) -> None:
result = runner.invoke(llamactl)
assert result.exit_code == | 0 | assert | numeric_literal | tests/cli/test_cli.py | test_root_command | 19 | null | |
run-llama/llama_deploy | from pathlib import Path
from llama_deploy.apiserver.deployment_config_parser import DeploymentConfig
def do_assert(config: DeploymentConfig) -> None:
assert config.name == "MyDeployment"
assert config.default_service == "myworkflow"
wf_config = config.services["myworkflow"]
assert wf_config.name == ... | 1313 | assert | numeric_literal | tests/apiserver/test_config_parser.py | do_assert | 16 | null | |
run-llama/llama_deploy | import asyncio
import json
import subprocess
import sys
from collections.abc import Generator
from copy import deepcopy
from pathlib import Path
from typing import Any
from unittest import mock
import pytest
from workflows import Context, Workflow
from workflows.handler import WorkflowHandler
from llama_deploy.apiser... | 10 | assert | numeric_literal | tests/apiserver/test_deployment.py | test_manager_ctor | 440 | null | |
run-llama/llama_deploy | import io
from typing import Any
from unittest import mock
import httpx
import pytest
from llama_deploy.client.models.apiserver import (
ApiServer,
Deployment,
DeploymentCollection,
SessionCollection,
Task,
TaskCollection,
)
from llama_deploy.types import SessionDefinition, TaskDefinition, Tas... | "Unhealthy" | assert | string_literal | tests/client/models/test_apiserver.py | test_status_unhealthy | 268 | null | |
run-llama/llama_deploy | import os
from pathlib import Path
from unittest.mock import MagicMock, mock_open, patch
import pytest
from click.testing import CliRunner
from tenacity import RetryError
from llama_deploy.apiserver.settings import settings
from llama_deploy.cli.serve import serve
def runner() -> CliRunner:
"""Fixture for invoki... | 5 | assert | numeric_literal | tests/cli/test_serve.py | test_serve_deployment_creation_fails | 165 | null | |
run-llama/llama_deploy | from unittest import mock
import httpx
from click.testing import CliRunner
from llama_deploy.cli import llamactl
def test_sessions_create_error(runner: CliRunner) -> None:
with mock.patch("llama_deploy.cli.sessions.Client") as mocked_client:
mocked_client.return_value.sync.apiserver.deployments.get.side_... | "Error: test error\n" | assert | string_literal | tests/cli/test_sessions.py | test_sessions_create_error | 45 | null |
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