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 |
|---|---|---|---|---|---|---|---|---|---|
deepseek-ai/smallpond | import glob
import os.path
import tempfile
import unittest
import pyarrow.parquet as parquet
from loguru import logger
from smallpond.io.arrow import (
RowRange,
build_batch_reader_from_files,
cast_columns_to_large_string,
dump_to_parquet_files,
load_from_parquet_files,
)
from smallpond.utility im... | reversed_cols) | self.assertEqual | variable | tests/test_arrow.py | test_change_ordering_of_columns | TestArrow | 156 | null |
deepseek-ai/smallpond | import os.path
import queue
import sys
import unittest
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime
from multiprocessing import Manager, Process
from typing import List, Optional
import fsspec
import numpy as np
import psutil
import pyarrow as arrow
import pyarrow.compute as pc
impor... | y) | assert_* | variable | tests/test_fabric.py | _compare_arrow_tables | TestFabric | 275 | null |
deepseek-ai/smallpond | import glob
import importlib
import tempfile
import unittest
from smallpond.io.arrow import cast_columns_to_large_string
from tests.test_fabric import TestFabric
class TestDeltaLake(TestFabric, unittest.TestCase):
def test_load_mixed_large_dtypes(self):
from deltalake import DeltaTable, write_deltalake
... | loaded_table.num_rows) | self.assertEqual | complex_expr | tests/test_deltalake.py | test_load_mixed_large_dtypes | TestDeltaLake | 41 | null |
deepseek-ai/smallpond | import multiprocessing
import multiprocessing.dummy
import multiprocessing.queues
import queue
import tempfile
import time
import unittest
from loguru import logger
from smallpond.execution.workqueue import (
WorkItem,
WorkQueue,
WorkQueueInMemory,
WorkQueueOnFilesystem,
)
from tests.test_fabric impor... | numCollected) | self.assertEqual | variable | tests/test_workqueue.py | test_multi_consumers | WorkQueueTestBase | 94 | null |
deepseek-ai/smallpond | from typing import List
import pandas as pd
import pyarrow as pa
import pytest
from smallpond.dataframe import Session
def test_random_shuffle(sp: Session):
df = sp.from_items(list(range(1000))).repartition(10, by_rows=True)
df = df.random_shuffle()
shuffled = [d["item"] for d in df.take_all()]
asse... | list(range(1000)) | assert | func_call | tests/test_dataframe.py | test_random_shuffle | 97 | null | |
deepseek-ai/smallpond | import functools
import os.path
import socket
import tempfile
import time
import unittest
from datetime import datetime
from typing import Iterable, List, Tuple
import pandas
import pyarrow as arrow
from loguru import logger
from pandas.core.api import DataFrame as DataFrame
from smallpond.common import GB, MB, split... | all(map(os.path.exists, exec_plan.final_output.resolved_paths))) | self.assertTrue | func_call | tests/test_execution.py | test_variable_length_input_datasets | TestExecution | 368 | null |
deepseek-ai/smallpond | import os.path
import queue
import sys
import unittest
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime
from multiprocessing import Manager, Process
from typing import List, Optional
import fsspec
import numpy as np
import psutil
import pyarrow as arrow
import pyarrow.compute as pc
impor... | actual.column_names) | self.assertEqual | complex_expr | tests/test_fabric.py | _compare_arrow_tables | TestFabric | 266 | null |
deepseek-ai/smallpond | from typing import List
import pandas as pd
import pyarrow as pa
import pytest
from smallpond.dataframe import Session
def test_count(sp: Session):
df = sp.from_items([1, 2, 3])
assert df.count() == | 3 | assert | numeric_literal | tests/test_dataframe.py | test_count | 131 | null | |
deepseek-ai/smallpond | import random
import subprocess
import time
import unittest
from typing import Iterable
from smallpond.utility import ConcurrentIter, execute_command
from tests.test_fabric import TestFabric
class TestUtility(TestFabric, unittest.TestCase):
def test_concurrent_iter_no_error(self):
def slow_iterator(iter: ... | sum(range(n))) | self.assertEqual | func_call | tests/test_utility.py | test_concurrent_iter_no_error | TestUtility | 21 | null |
deepseek-ai/smallpond | from typing import List
import pandas as pd
import pyarrow as pa
import pytest
from smallpond.dataframe import Session
def test_flat_map(sp: Session):
df = sp.from_arrow(pa.table({"a": [1, 2, 3], "b": [4, 5, 6]}))
df1 = df.flat_map(lambda r: [{"c": r["a"]}, {"c": r["b"]}])
assert df1.to_arrow() == | pa.table({"c": [1, 4, 2, 5, 3, 6]}) | assert | func_call | tests/test_dataframe.py | test_flat_map | 67 | null | |
deepseek-ai/smallpond | import os.path
import tempfile
import unittest
from typing import List
import pyarrow.compute as pc
from smallpond.common import DATA_PARTITION_COLUMN_NAME, GB
from smallpond.execution.task import RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.logical.node import (
Arr... | isinstance(final_output, ParquetDataSet)) | self.assertTrue | func_call | tests/test_partition.py | test_empty_dataset_partition | TestPartition | 98 | null |
deepseek-ai/smallpond | import glob
import os.path
import tempfile
import unittest
import pyarrow.parquet as parquet
from loguru import logger
from smallpond.io.arrow import (
RowRange,
build_batch_reader_from_files,
cast_columns_to_large_string,
dump_to_parquet_files,
load_from_parquet_files,
)
from smallpond.utility im... | 0) | self.assertEqual | numeric_literal | tests/test_arrow.py | test_dump_load_empty_table | TestArrow | 69 | null |
deepseek-ai/smallpond | import unittest
from loguru import logger
from smallpond.logical.dataset import ParquetDataSet
from smallpond.logical.node import (
Context,
DataSetPartitionNode,
DataSourceNode,
EvenlyDistributedPartitionNode,
HashPartitionNode,
LogicalPlan,
SqlEngineNode,
)
from smallpond.logical.planner... | AssertionError) | self.assertRaises | variable | tests/test_logical.py | test_partition_dims_not_compatible | TestLogicalPlan | 57 | null |
deepseek-ai/smallpond | from typing import List
import pandas as pd
import pyarrow as pa
import pytest
from smallpond.dataframe import Session
def test_partial_sql(sp: Session):
# no input deps
df = sp.partial_sql("select * from range(3)")
assert df.to_arrow() == | pa.table({"range": [0, 1, 2]}) | assert | func_call | tests/test_dataframe.py | test_partial_sql | 151 | null | |
deepseek-ai/smallpond | import functools
import os.path
import socket
import tempfile
import time
import unittest
from datetime import datetime
from typing import Iterable, List, Tuple
import pandas
import pyarrow as arrow
from loguru import logger
from pandas.core.api import DataFrame as DataFrame
from smallpond.common import GB, MB, split... | exec_plan.get_output("random_urls_k5").to_arrow_table().num_rows) | self.assertEqual | func_call | tests/test_execution.py | test_partial_process_func | TestExecution | 751 | null |
deepseek-ai/smallpond | import functools
import os.path
import socket
import tempfile
import time
import unittest
from datetime import datetime
from typing import Iterable, List, Tuple
import pandas
import pyarrow as arrow
from loguru import logger
from pandas.core.api import DataFrame as DataFrame
from smallpond.common import GB, MB, split... | final_output.num_rows) | self.assertEqual | complex_expr | tests/test_execution.py | test_temp_outputs_in_final_results | TestExecution | 652 | null |
deepseek-ai/smallpond | import functools
import os.path
import socket
import tempfile
import time
import unittest
from datetime import datetime
from typing import Iterable, List, Tuple
import pandas
import pyarrow as arrow
from loguru import logger
from pandas.core.api import DataFrame as DataFrame
from smallpond.common import GB, MB, split... | num_lines) | self.assertEqual | variable | tests/test_execution.py | test_manifest_only_data_sink | TestExecution | 591 | null |
deepseek-ai/smallpond | import glob
import os.path
import unittest
from pathlib import PurePath
import duckdb
import pandas
import pyarrow as arrow
import pytest
from loguru import logger
from smallpond.common import DEFAULT_ROW_GROUP_SIZE, MB
from smallpond.logical.dataset import ParquetDataSet
from smallpond.utility import ConcurrentIter
... | loaded_table.shape) | self.assertEqual | complex_expr | tests/test_dataset.py | _check_partition_datasets | TestDataSet | 55 | null |
deepseek-ai/smallpond | import functools
import os.path
import socket
import tempfile
import time
import unittest
from datetime import datetime
from typing import Iterable, List, Tuple
import pandas
import pyarrow as arrow
from loguru import logger
from pandas.core.api import DataFrame as DataFrame
from smallpond.common import GB, MB, split... | os.path.exists(os.path.join(output_path, "FinalResults"))) | self.assertTrue | func_call | tests/test_execution.py | test_override_output_path | TestExecution | 679 | null |
deepseek-ai/smallpond | import os.path
import tempfile
import unittest
from typing import List
import pyarrow.compute as pc
from smallpond.common import DATA_PARTITION_COLUMN_NAME, GB
from smallpond.execution.task import RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.logical.node import (
Arr... | len(exec_plan.final_output.load_partitioned_datasets(npartitions, "hash_partitions"))) | self.assertEqual | func_call | tests/test_partition.py | test_empty_hash_partition | TestPartition | 216 | null |
deepseek-ai/smallpond | import glob
import os.path
import tempfile
import unittest
import pyarrow.parquet as parquet
from loguru import logger
from smallpond.io.arrow import (
RowRange,
build_batch_reader_from_files,
cast_columns_to_large_string,
dump_to_parquet_files,
load_from_parquet_files,
)
from smallpond.utility im... | loaded_table.schema.metadata) | self.assertEqual | complex_expr | tests/test_arrow.py | test_arrow_schema_metadata | TestArrow | 125 | null |
deepseek-ai/smallpond | import os.path
import tempfile
import unittest
from typing import List
import pyarrow.compute as pc
from smallpond.common import DATA_PARTITION_COLUMN_NAME, GB
from smallpond.execution.task import RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.logical.node import (
Arr... | len(exec_plan.final_output.load_partitioned_datasets(npartitions, DATA_PARTITION_COLUMN_NAME))) | self.assertEqual | func_call | tests/test_partition.py | test_hash_partition | TestPartition | 144 | null |
deepseek-ai/smallpond | import itertools
import unittest
import numpy as np
from hypothesis import given
from hypothesis import strategies as st
from smallpond.common import get_nth_partition, split_into_cols, split_into_rows
from tests.test_fabric import TestFabric
class TestCommon(TestFabric, unittest.TestCase):
def test_get_nth_part... | get_nth_partition(items, 0, 3)) | self.assertListEqual | func_call | tests/test_common.py | test_get_nth_partition | TestCommon | 21 | null |
deepseek-ai/smallpond | import os.path
import queue
import sys
import unittest
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime
from multiprocessing import Manager, Process
from typing import List, Optional
import fsspec
import numpy as np
import psutil
import pyarrow as arrow
import pyarrow.compute as pc
impor... | latest_state.success) | self.assertTrue | complex_expr | tests/test_fabric.py | execute_plan | TestFabric | 251 | null |
deepseek-ai/smallpond | import os.path
import tempfile
import unittest
from typing import List
import pyarrow.compute as pc
from smallpond.common import DATA_PARTITION_COLUMN_NAME, GB
from smallpond.execution.task import RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.logical.node import (
Arr... | len( exec_plan.get_output("hash_partitions").load_partitioned_datasets( npartitions, DATA_PARTITION_COLUMN_NAME, hive_partitioning, ) )) | self.assertEqual | func_call | tests/test_partition.py | test_hash_partition | TestPartition | 148 | null |
deepseek-ai/smallpond | import os.path
import tempfile
import unittest
from typing import List
import pyarrow.compute as pc
from smallpond.common import DATA_PARTITION_COLUMN_NAME, GB
from smallpond.execution.task import RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.logical.node import (
Arr... | final_output.num_rows) | self.assertEqual | complex_expr | tests/test_partition.py | test_empty_dataset_partition | TestPartition | 99 | null |
deepseek-ai/smallpond | import glob
import os.path
import unittest
from pathlib import PurePath
import duckdb
import pandas
import pyarrow as arrow
import pytest
from loguru import logger
from smallpond.common import DEFAULT_ROW_GROUP_SIZE, MB
from smallpond.logical.dataset import ParquetDataSet
from smallpond.utility import ConcurrentIter
... | dataset.num_rows) | self.assertEqual | complex_expr | tests/test_dataset.py | test_parquet_file_created_by_pandas | TestDataSet | 31 | null |
deepseek-ai/smallpond | import random
import subprocess
import time
import unittest
from typing import Iterable
from smallpond.utility import ConcurrentIter, execute_command
from tests.test_fabric import TestFabric
class TestUtility(TestFabric, unittest.TestCase):
def test_execute_command(self):
with self.assertRaises( | subprocess.CalledProcessError) | self.assertRaises | complex_expr | tests/test_utility.py | test_execute_command | TestUtility | 44 | null |
deepseek-ai/smallpond | import os.path
import random
import time
import unittest
from typing import List, Tuple
from loguru import logger
from smallpond.execution.scheduler import ExecutorState
from smallpond.execution.task import PythonScriptTask, RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.l... | f"remote_executors: {latest_sched_state.remote_executors}") | self.assertLessEqual | string_literal | tests/test_scheduler.py | test_failed_executors | TestScheduler | 121 | null |
deepseek-ai/smallpond | import glob
import os.path
import tempfile
import unittest
import pyarrow.parquet as parquet
from loguru import logger
from smallpond.io.arrow import (
RowRange,
build_batch_reader_from_files,
cast_columns_to_large_string,
dump_to_parquet_files,
load_from_parquet_files,
)
from smallpond.utility im... | dump_to_parquet_files(table_with_meta, output_dir, "arrow_schema_metadata", max_workers=2)) | self.assertTrue | func_call | tests/test_arrow.py | test_arrow_schema_metadata | TestArrow | 121 | null |
deepseek-ai/smallpond | import functools
import os.path
import socket
import tempfile
import time
import unittest
from datetime import datetime
from typing import Iterable, List, Tuple
import pandas
import pyarrow as arrow
from loguru import logger
from pandas.core.api import DataFrame as DataFrame
from smallpond.common import GB, MB, split... | exec_plan.successful) | self.assertFalse | complex_expr | tests/test_execution.py | test_task_crash_as_oom | TestExecution | 568 | null |
deepseek-ai/smallpond | import glob
import os.path
import tempfile
import unittest
import pyarrow.parquet as parquet
from loguru import logger
from smallpond.io.arrow import (
RowRange,
build_batch_reader_from_files,
cast_columns_to_large_string,
dump_to_parquet_files,
load_from_parquet_files,
)
from smallpond.utility im... | ok) | self.assertTrue | variable | tests/test_arrow.py | test_dump_load_empty_table | TestArrow | 73 | null |
deepseek-ai/smallpond | import glob
import os.path
import tempfile
import unittest
import pyarrow.parquet as parquet
from loguru import logger
from smallpond.io.arrow import (
RowRange,
build_batch_reader_from_files,
cast_columns_to_large_string,
dump_to_parquet_files,
load_from_parquet_files,
)
from smallpond.utility im... | expected_num_rows) | self.assertEqual | variable | tests/test_arrow.py | test_parquet_batch_reader | TestArrow | 97 | null |
deepseek-ai/smallpond | import glob
import os.path
import unittest
from pathlib import PurePath
import duckdb
import pandas
import pyarrow as arrow
import pytest
from loguru import logger
from smallpond.common import DEFAULT_ROW_GROUP_SIZE, MB
from smallpond.logical.dataset import ParquetDataSet
from smallpond.utility import ConcurrentIter
... | len(filenames)) | self.assertEqual | func_call | tests/test_dataset.py | test_resolved_many_paths | TestDataSet | 102 | null |
deepseek-ai/smallpond | import os.path
import tempfile
import unittest
from typing import List
import pyarrow.compute as pc
from smallpond.common import DATA_PARTITION_COLUMN_NAME, GB
from smallpond.execution.task import RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.logical.node import (
Arr... | len(final_output_partitions3)) | self.assertEqual | func_call | tests/test_partition.py | test_load_partitioned_datasets | TestPartition | 350 | null |
deepseek-ai/smallpond | import glob
import os.path
import tempfile
import unittest
import pyarrow.parquet as parquet
from loguru import logger
from smallpond.io.arrow import (
RowRange,
build_batch_reader_from_files,
cast_columns_to_large_string,
dump_to_parquet_files,
load_from_parquet_files,
)
from smallpond.utility im... | AssertionError) | self.assertRaises | variable | tests/test_arrow.py | test_load_not_exist_column | TestArrow | 148 | null |
deepseek-ai/smallpond | import random
import subprocess
import time
import unittest
from typing import Iterable
from smallpond.utility import ConcurrentIter, execute_command
from tests.test_fabric import TestFabric
class TestUtility(TestFabric, unittest.TestCase):
def test_concurrent_iter_with_error(self):
def broken_iterator(i... | Exception) | self.assertRaises | variable | tests/test_utility.py | test_concurrent_iter_with_error | TestUtility | 35 | null |
deepseek-ai/smallpond | import os.path
import random
import time
import unittest
from typing import List, Tuple
from loguru import logger
from smallpond.execution.scheduler import ExecutorState
from smallpond.execution.task import PythonScriptTask, RuntimeContext
from smallpond.logical.dataset import DataSet, ParquetDataSet
from smallpond.l... | False) | self.assertTrue | bool_literal | tests/test_scheduler.py | check_executor_state | TestScheduler | 85 | null |
deepseek-ai/smallpond | import itertools
import unittest
import numpy as np
from hypothesis import given
from hypothesis import strategies as st
from smallpond.common import get_nth_partition, split_into_cols, split_into_rows
from tests.test_fabric import TestFabric
class TestCommon(TestFabric, unittest.TestCase):
def test_get_nth_part... | get_nth_partition(items, 0, 1)) | self.assertListEqual | func_call | tests/test_common.py | test_get_nth_partition | TestCommon | 16 | null |
deepseek-ai/smallpond | import itertools
import unittest
import numpy as np
from hypothesis import given
from hypothesis import strategies as st
from smallpond.common import get_nth_partition, split_into_cols, split_into_rows
from tests.test_fabric import TestFabric
class TestCommon(TestFabric, unittest.TestCase):
@given(st.data())
... | chunk_size * npartitions) | self.assertEqual | complex_expr | tests/test_common.py | test_split_into_cols | TestCommon | 57 | null |
deepseek-ai/smallpond | import glob
import os.path
import unittest
from pathlib import PurePath
import duckdb
import pandas
import pyarrow as arrow
import pytest
from loguru import logger
from smallpond.common import DEFAULT_ROW_GROUP_SIZE, MB
from smallpond.logical.dataset import ParquetDataSet
from smallpond.utility import ConcurrentIter
... | DEFAULT_ROW_GROUP_SIZE * 2) | self.assertLessEqual | complex_expr | tests/test_dataset.py | test_to_arrow_table_batch_reader | TestDataSet | 129 | null |
nerfbaselines/nerfbaselines | import numpy as np
import pytest
import platform
import plyfile
import urllib.request
def test_viewer_simple_http_server():
# Skip test on windows
if platform.system() == "Windows":
pytest.skip("Windows needs to be tested first.")
from nerfbaselines.viewer import Viewer
dataset = {
"p... | 200 | assert | numeric_literal | tests/test_viewer.py | test_viewer_simple_http_server | 26 | null | |
nerfbaselines/nerfbaselines | import contextlib
import sys
import shutil
import json
from typing import cast
from pathlib import Path
import os
import numpy as np
from nerfbaselines import Method, MethodInfo, Cameras, RenderOutput, ModelInfo
from nerfbaselines.utils import Indices
from nerfbaselines.datasets import _colmap_utils as colmap_utils
fro... | None | assert | none_literal | tests/test_train_render.py | test_train_command_undistort | 307 | null | |
nerfbaselines/nerfbaselines | from contextlib import nullcontext
import shutil
import subprocess
import importlib
import gc
import copy
import tarfile
import json
import sys
import pickle
from functools import partial
import inspect
from unittest import mock
import contextlib
import os
import pytest
from pathlib import Path
import numpy as np
from ... | weight.shape[0] | assert | complex_expr | tests/conftest.py | conv2d | 855 | null | |
nerfbaselines/nerfbaselines | import pytest
import numpy as np
from nerfbaselines import cameras
from nerfbaselines import camera_model_to_int, CameraModel, new_cameras
from nerfbaselines._types import _get_xnp
def _build_camera(camera_model: CameraModel, intrinsics, distortion_parameters=None, image_sizes=None):
if image_sizes is None:
... | xy0) | assert_* | variable | tests/test_cameras.py | _test_cam_from_img_to_img | 133 | null | |
nerfbaselines/nerfbaselines | import os
import pytest
from nerfbaselines import get_supported_methods, get_method_spec
@pytest.mark.parametrize("method_name", [pytest.param(k, marks=[pytest.mark.method(k)]) for k in get_supported_methods("docker")])
def test_docker_get_dockerfile(method_name):
from nerfbaselines.backends._docker import docker_... | 0 | assert | numeric_literal | tests/test_backends.py | test_docker_get_dockerfile | 14 | null | |
nerfbaselines/nerfbaselines | import importlib.resources
import sys
from typing import cast
import numpy as np
import pytest
from nerfbaselines.metrics import torchmetrics_ssim, dmpix_ssim
from nerfbaselines import metrics
@pytest.mark.extras
@pytest.mark.filterwarnings("ignore::UserWarning:torchvision")
@pytest.mark.parametrize("kernel_size", [No... | (3,) | assert | collection | tests/test_metrics.py | test_torchmetrics_ssim | 45 | null | |
nerfbaselines/nerfbaselines | import importlib.resources
import sys
from typing import cast
import numpy as np
import pytest
from nerfbaselines.metrics import torchmetrics_ssim, dmpix_ssim
from nerfbaselines import metrics
@pytest.mark.filterwarnings("ignore::UserWarning:torchvision")
@pytest.mark.parametrize("metric", ["torchmetrics_ssim", "dmpix... | Exception) | pytest.raises | variable | tests/test_metrics.py | test_metric | 106 | null | |
nerfbaselines/nerfbaselines | import json
from pathlib import Path
def test_open_any_directory(tmp_path):
from nerfbaselines.io import open_any_directory, open_any
with open_any_directory(tmp_path / "data.zip/obj.tar.gz/test/test.zip/ok/pass.zip", "w") as _path:
path = Path(_path)
(path / "data.txt").write_text("Hello worl... | b"Hello world2" | assert | string_literal | tests/test_io.py | test_open_any_directory | 50 | null | |
nerfbaselines/nerfbaselines | from contextlib import nullcontext
import shutil
import subprocess
import importlib
import gc
import copy
import tarfile
import json
import sys
import pickle
from functools import partial
import inspect
from unittest import mock
import contextlib
import os
import pytest
from pathlib import Path
import numpy as np
from ... | test_name | assert | variable | tests/conftest.py | run_test_train_fixture | 309 | null | |
nerfbaselines/nerfbaselines | import numpy as np
from unittest import mock
import pytest
from time import sleep, perf_counter
from nerfbaselines.utils import Indices
from nerfbaselines.utils import CancellationToken, CancelledException
def test_tuple_click_type():
import click
from nerfbaselines.cli._common import TupleClickType
with ... | SystemExit) | pytest.raises | variable | tests/test_utils.py | test_tuple_click_type | 87 | null | |
nerfbaselines/nerfbaselines | import contextlib
import traceback
import sys
import json
import glob
import pprint
import logging
import os
import numpy as np
import click
from PIL import Image
import tempfile
from tqdm import trange
import nerfbaselines
from typing import Type
import urllib.request
from nerfbaselines import (
build_method_class... | steps | assert | variable | nerfbaselines/cli/_test_method.py | main | 332 | null | |
nerfbaselines/nerfbaselines | import importlib.resources
import sys
from typing import cast
import numpy as np
import pytest
from nerfbaselines.metrics import torchmetrics_ssim, dmpix_ssim
from nerfbaselines import metrics
def test_psnr():
np.random.seed(42)
batch_shapes = [
(3,),
(2, 2),
(
2,
... | val2) | assert_* | variable | tests/test_metrics.py | test_psnr | 141 | null | |
nerfbaselines/nerfbaselines | import numpy as np
from unittest import mock
import pytest
from time import sleep, perf_counter
from nerfbaselines.utils import Indices
from nerfbaselines.utils import CancellationToken, CancelledException
def test_convert_image_dtype_numpy():
from nerfbaselines.utils import convert_image_dtype
# Test keep sa... | 1e-5 | assert | numeric_literal | tests/test_utils.py | test_convert_image_dtype_numpy | 131 | null | |
nerfbaselines/nerfbaselines | import importlib
import numpy as np
import copy
import argparse
import sys
import os
import pytest
METHOD_NAME = "taming-3dgs"
def taming_source_code(load_source_code):
load_source_code("https://github.com/humansensinglab/taming-3dgs.git", "446f2c0d50d082e660e5b899d304da5931351dec")
def colmap_dataset(colmap_dat... | splats | assert | variable | tests/methods/test_taming_3dgs.py | _test_taming_3dgs | 117 | null | |
nerfbaselines/nerfbaselines | import numpy as np
from unittest import mock
import pytest
from time import sleep, perf_counter
from nerfbaselines.utils import Indices
from nerfbaselines.utils import CancellationToken, CancelledException
def test_convert_image_dtype_numpy():
from nerfbaselines.utils import convert_image_dtype
# Test keep sa... | arr | assert | variable | tests/test_utils.py | test_convert_image_dtype_numpy | 121 | null | |
nerfbaselines/nerfbaselines | import time
import sys
import contextlib
import threading
import pytest
import functools
import signal
def _signal_handler(signum, frame):
del signum, frame
pytest.fail("Timeout")
def timeout(timeout):
def decorator(fn):
@functools.wraps(fn)
def wrapper(*args, **kwargs):
if not... | 4 | assert | numeric_literal | tests/test_rpc_protocol.py | test_protocol_large_message | 149 | null | |
nerfbaselines/nerfbaselines | from functools import partial
from unittest import mock
import contextlib
import pytest
from typing import Iterable
import numpy as np
from time import sleep
from nerfbaselines import Method, MethodInfo, RenderOutput, ModelInfo, new_cameras
from nerfbaselines.utils import CancellationToken, CancelledException
def test... | 23 | assert | numeric_literal | tests/test_communication.py | test_render | 47 | null | |
nerfbaselines/nerfbaselines | import sys
import contextlib
import logging
from unittest import mock
import math
from typing import List, Dict, Any, cast, Union, Type, Iterator, Optional, Tuple
import base64
import os
import struct
from pathlib import Path
import json
import warnings
import numpy as np
from .io import open_any
from . import (
me... | tuple(supported_outputs) | assert | func_call | nerfbaselines/results.py | get_method_info_from_spec | 193 | null | |
nerfbaselines/nerfbaselines | import os
from unittest import mock
import contextlib
import numpy as np
import pytest
from nerfbaselines import (
get_supported_methods,
get_method_spec,
)
from nerfbaselines.training import (
get_presets_and_config_overrides,
)
from nerfbaselines import build_method_class
from nerfbaselines.datasets impor... | None | assert | none_literal | tests/test_methods.py | test_method_conda | 84 | null | |
nerfbaselines/nerfbaselines | import numpy as np
from unittest import mock
import pytest
from time import sleep, perf_counter
from nerfbaselines.utils import Indices
from nerfbaselines.utils import CancellationToken, CancelledException
@click.command()
@click.option("--val", type=TupleClickType(), default=None)
def cmd(val)... | None | assert | none_literal | tests/test_utils.py | cmd | 91 | null | |
nerfbaselines/nerfbaselines | from enum import Enum
from pathlib import Path
import tempfile
import pytest
import contextlib
import numpy as np
import sys
from unittest import mock
METHOD_NAME = "instant-ngp"
def _set_camera_to_training_view(x):
nonlocal test_view
assert image_sizes is not | None | assert | none_literal | tests/methods/_test_ingp.py | _set_camera_to_training_view | 47 | null | |
nerfbaselines/nerfbaselines | import contextlib
import sys
import shutil
import json
from typing import cast
from pathlib import Path
import os
import numpy as np
from nerfbaselines import Method, MethodInfo, Cameras, RenderOutput, ModelInfo
from nerfbaselines.utils import Indices
from nerfbaselines.datasets import _colmap_utils as colmap_utils
fro... | 0 | assert | numeric_literal | tests/test_train_render.py | render | _Method | 326 | null |
nerfbaselines/nerfbaselines | import pytest
import os
from functools import partial
import threading
import pytest
import time
from time import sleep
import gc
from unittest import mock
from nerfbaselines.utils import CancelledException, CancellationToken
from nerfbaselines.backends._common import SimpleBackend
from nerfbaselines import backends
... | 0 | assert | numeric_literal | tests/test_rpc.py | test_rpc_backend_yield | 186 | null | |
nerfbaselines/nerfbaselines | import unittest.mock
import importlib
import numpy as np
import copy
import argparse
import os
import pytest
METHOD_NAME = "hierarchical-3dgs"
def dataloader_noworkers():
from torch.utils.data import DataLoader
old_init = DataLoader.__init__
def dl_init(self, *args, **kwargs):
kwargs["num_workers"... | render | assert | variable | tests/methods/test_hierarchical_3dgs.py | _test_hierarchical_3dgs | 144 | null | |
nerfbaselines/nerfbaselines | import json
import sys
import pytest
from typing import Any, cast
from unittest import mock
from nerfbaselines import get_supported_methods, get_supported_datasets
from nerfbaselines.results import render_markdown_dataset_results_table
def mock_results(results_path, datasets, methods):
from nerfbaselines import ge... | k) | assert_* | variable | tests/test_results.py | assert_ok_type | 104 | null | |
nerfbaselines/nerfbaselines | import time
import sys
import contextlib
import threading
import pytest
import functools
import signal
def _signal_handler(signum, frame):
del signum, frame
pytest.fail("Timeout")
def timeout(timeout):
def decorator(fn):
@functools.wraps(fn)
def wrapper(*args, **kwargs):
if not... | TimeoutError) | pytest.raises | variable | tests/test_rpc_protocol.py | test_protocol_wait_for_worker_timeout | 38 | null | |
nerfbaselines/nerfbaselines | from pathlib import Path
from collections import defaultdict
import os
from dataclasses import dataclass, field
from typing import Any, cast
import enum
import pytest
import sys
from unittest import mock
def setup():
assert config is not | None | assert | none_literal | tests/methods/_test_nerfstudio.py | setup | 132 | null | |
nerfbaselines/nerfbaselines | import json
import sys
import pytest
from typing import Any, cast
from unittest import mock
from nerfbaselines import get_supported_methods, get_supported_datasets
from nerfbaselines.results import render_markdown_dataset_results_table
def mock_results(results_path, datasets, methods):
from nerfbaselines import ge... | method | assert | variable | tests/test_results.py | assert_compile_dataset_results_correct | 74 | null | |
nerfbaselines/nerfbaselines | import time
import sys
import contextlib
import threading
import pytest
import functools
import signal
def _signal_handler(signum, frame):
del signum, frame
pytest.fail("Timeout")
def timeout(timeout):
def decorator(fn):
@functools.wraps(fn)
def wrapper(*args, **kwargs):
if not... | ConnectionError) | pytest.raises | variable | tests/test_rpc_protocol.py | test_protocol_close_connection_worker | 216 | null | |
nerfbaselines/nerfbaselines | import pytest
import os
import numpy as np
from typing import Optional, TypeVar
from unittest import mock
from unittest.mock import MagicMock
from nerfbaselines import Method, new_cameras
from nerfbaselines import evaluation
from PIL import Image
import tarfile
import zipfile
T = TypeVar("T")
def _assert_not_none(val... | num_cams | assert | variable | tests/test_render_frames.py | _verify_folder_single | 311 | null | |
nerfbaselines/nerfbaselines | import os
from unittest import mock
import contextlib
import numpy as np
import pytest
from nerfbaselines import (
get_supported_methods,
get_method_spec,
)
from nerfbaselines.training import (
get_presets_and_config_overrides,
)
from nerfbaselines import build_method_class
from nerfbaselines.datasets impor... | 0 | assert | numeric_literal | tests/test_methods.py | test_supported_methods | 25 | null | |
nerfbaselines/nerfbaselines | import importlib.resources
import sys
from typing import cast
import numpy as np
import pytest
from nerfbaselines.metrics import torchmetrics_ssim, dmpix_ssim
from nerfbaselines import metrics
@pytest.mark.filterwarnings("ignore::UserWarning:torchvision")
@pytest.mark.parametrize("metric", ["torchmetrics_ssim", "dmpix... | bs | assert | variable | tests/test_metrics.py | test_metric | 103 | null | |
nerfbaselines/nerfbaselines | import os
from unittest import mock
import contextlib
import numpy as np
import pytest
from nerfbaselines import (
get_supported_methods,
get_method_spec,
)
from nerfbaselines.training import (
get_presets_and_config_overrides,
)
from nerfbaselines import build_method_class
from nerfbaselines.datasets impor... | "conda" | assert | string_literal | tests/test_methods.py | test_method_conda | 85 | null | |
nerfbaselines/nerfbaselines | import contextlib
import sys
import shutil
import json
from typing import cast
from pathlib import Path
import os
import numpy as np
from nerfbaselines import Method, MethodInfo, Cameras, RenderOutput, ModelInfo
from nerfbaselines.utils import Indices
from nerfbaselines.datasets import _colmap_utils as colmap_utils
fro... | 13 | assert | numeric_literal | tests/test_train_render.py | test_train_command_extras | 265 | null | |
nerfbaselines/nerfbaselines | import pytest
import os
import sys
import contextlib
from unittest import mock
from nerfbaselines import Method, MethodInfo, ModelInfo
import numpy as np
def clear_allowed_methods():
allowed_methods = os.environ.get("NERFBASELINES_ALLOWED_METHODS", None)
try:
os.environ.pop("NERFBASELINES_ALLOWED_METHO... | set(()) | assert | func_call | tests/test_registry.py | test_get_presets_to_apply | 146 | null | |
nerfbaselines/nerfbaselines | import pytest
import numpy as np
from nerfbaselines import cameras
from nerfbaselines import camera_model_to_int, CameraModel, new_cameras
from nerfbaselines._types import _get_xnp
@pytest.mark.parametrize("camera_type", get_args(CameraModel))
def test_camera(camera_type):
np.random.seed(42)
num_cam = 10
r... | xy_new) | assert_* | variable | tests/test_cameras.py | test_camera | 50 | null | |
nerfbaselines/nerfbaselines | import json
from pathlib import Path
def test_load_and_save_trajectory(tmp_path):
from nerfbaselines import io
pose = [0.568, -0.102, 0.816, -11.05, 0.178, 0.983, -0.001, 0.059, -0.802, 0.146, 0.577, -7.812]
frame = {
"pose": pose,
"intrinsics": [623.53, 623.53, 640.0, 360.0],
"app... | 3 | assert | numeric_literal | tests/test_io.py | test_load_and_save_trajectory | 94 | null | |
nerfbaselines/nerfbaselines | import contextlib
import traceback
import sys
import json
import glob
import pprint
import logging
import os
import numpy as np
import click
from PIL import Image
import tempfile
from tqdm import trange
import nerfbaselines
from typing import Type
import urllib.request
from nerfbaselines import (
build_method_class... | im2) | assert_* | variable | nerfbaselines/cli/_test_method.py | main | 472 | null | |
nerfbaselines/nerfbaselines | import importlib.resources
import sys
from typing import cast
import numpy as np
import pytest
from nerfbaselines.metrics import torchmetrics_ssim, dmpix_ssim
from nerfbaselines import metrics
@pytest.mark.extras
@pytest.mark.filterwarnings("ignore::UserWarning:torchvision")
@pytest.mark.parametrize("kernel_size", [No... | reference2) | assert_* | variable | tests/test_metrics.py | test_torchmetrics_ssim | 51 | null | |
nerfbaselines/nerfbaselines | import pytest
import numpy as np
from nerfbaselines import cameras
from nerfbaselines import camera_model_to_int, CameraModel, new_cameras
from nerfbaselines._types import _get_xnp
def _build_camera(camera_model: CameraModel, intrinsics, distortion_parameters=None, image_sizes=None):
if image_sizes is None:
... | uv0) | assert_* | variable | tests/test_cameras.py | _test_cam_to_cam_from_img | 123 | null | |
nerfbaselines/nerfbaselines | import importlib.resources
import sys
from typing import cast
import numpy as np
import pytest
from nerfbaselines.metrics import torchmetrics_ssim, dmpix_ssim
from nerfbaselines import metrics
@pytest.mark.filterwarnings("ignore::UserWarning:torchvision")
@pytest.mark.parametrize("metric", ["torchmetrics_ssim", "dmpix... | (*bs, 47-10, 31-10, 3) | assert | collection | tests/test_metrics.py | test_metric | 114 | null | |
nerfbaselines/nerfbaselines | import json
import sys
import pytest
from typing import Any, cast
from unittest import mock
from nerfbaselines import get_supported_methods, get_supported_datasets
from nerfbaselines.results import render_markdown_dataset_results_table
def mock_results(results_path, datasets, methods):
from nerfbaselines import ge... | datasets | assert | variable | tests/test_results.py | test_get_supported_datasets | 43 | null | |
nerfbaselines/nerfbaselines | import json
import sys
import pytest
from typing import Any, cast
from unittest import mock
from nerfbaselines import get_supported_methods, get_supported_datasets
from nerfbaselines.results import render_markdown_dataset_results_table
def mock_results(results_path, datasets, methods):
from nerfbaselines import ge... | y) | assert_* | variable | tests/test_results.py | assert_ok_type | 100 | null | |
nerfbaselines/nerfbaselines | import contextlib
import traceback
import sys
import json
import glob
import pprint
import logging
import os
import numpy as np
import click
from PIL import Image
import tempfile
from tqdm import trange
import nerfbaselines
from typing import Type
import urllib.request
from nerfbaselines import (
build_method_class... | render2_out | assert | variable | nerfbaselines/cli/_test_method.py | test_render | 364 | null | |
nerfbaselines/nerfbaselines | import pytest
import numpy as np
from nerfbaselines import cameras
from nerfbaselines import camera_model_to_int, CameraModel, new_cameras
from nerfbaselines._types import _get_xnp
def _build_camera(camera_model: CameraModel, intrinsics, distortion_parameters=None, image_sizes=None):
if image_sizes is None:
... | np.int32 | assert | complex_expr | tests/test_cameras.py | test_get_image_pixels_shape | 214 | null | |
nerfbaselines/nerfbaselines | import pytest
import numpy as np
from nerfbaselines import cameras
from nerfbaselines import camera_model_to_int, CameraModel, new_cameras
from nerfbaselines._types import _get_xnp
def _build_camera(camera_model: CameraModel, intrinsics, distortion_parameters=None, image_sizes=None):
if image_sizes is None:
... | None | assert | none_literal | tests/test_cameras.py | test_camera_undistort_opencv | 205 | null | |
nerfbaselines/nerfbaselines | import logging
import shutil
import ast
import sys
import os
import contextlib
import json
from typing import Optional, Dict
from nerfbaselines import Method, Dataset, MethodInfo, ModelInfo, RenderOutput, Cameras
from nerfbaselines.datasets import _colmap_utils as colmap_utils
from nerfbaselines.datasets import colmap ... | None | assert | none_literal | nerfbaselines/methods/threedgrut.py | _get_train_iteration | 73 | null | |
nerfbaselines/nerfbaselines | import numpy as np
import pytest
import platform
import plyfile
import urllib.request
def test_viewer_simple_http_server():
# Skip test on windows
if platform.system() == "Windows":
pytest.skip("Windows needs to be tested first.")
from nerfbaselines.viewer import Viewer
dataset = {
"p... | None | assert | none_literal | tests/test_viewer.py | test_viewer_simple_http_server | 21 | null | |
nerfbaselines/nerfbaselines | import pytest
import os
from functools import partial
import threading
import pytest
import time
from time import sleep
import gc
from unittest import mock
from nerfbaselines.utils import CancelledException, CancellationToken
from nerfbaselines.backends._common import SimpleBackend
from nerfbaselines import backends
... | 1 | assert | numeric_literal | tests/test_rpc.py | test_rpc_backend_instance | 126 | null | |
nerfbaselines/nerfbaselines | _patch = """diff --git a/scene/__init__.py b/scene/__init__.py
index 2b31398..c31679a 100644
--- a/scene/__init__.py
+++ b/scene/__init__.py
@@ -25 +25 @@ class Scene:
- def __init__(self, args : ModelParams, gaussians : GaussianModel, load_iteration=None, shuffle=True, resolution_scales=[1.0]):
+ def __init__(se... | after | assert | variable | tests/test_patching.py | test_apply_patch | 65 | null | |
nerfbaselines/nerfbaselines | from unittest import mock
import importlib
import numpy as np
import copy
import argparse
import os
import pytest
from PIL import Image
import matplotlib.pyplot
from nerfbaselines._registry import collect_register_calls
METHOD_ID = "sparsegs"
def method_source_code(load_source_code):
with collect_register_calls(... | render | assert | variable | tests/methods/test_sparsegs.py | _test_method | 135 | null | |
nerfbaselines/nerfbaselines | import pytest
import os
import sys
import contextlib
from unittest import mock
from nerfbaselines import Method, MethodInfo, ModelInfo
import numpy as np
def clear_allowed_methods():
allowed_methods = os.environ.get("NERFBASELINES_ALLOWED_METHODS", None)
try:
os.environ.pop("NERFBASELINES_ALLOWED_METHO... | 1 | assert | numeric_literal | tests/test_registry.py | test_register_environment_variable | 300 | null | |
nerfbaselines/nerfbaselines | import os
from unittest import mock
import contextlib
import numpy as np
import pytest
from nerfbaselines import (
get_supported_methods,
get_method_spec,
)
from nerfbaselines.training import (
get_presets_and_config_overrides,
)
from nerfbaselines import build_method_class
from nerfbaselines.datasets impor... | methods | assert | variable | tests/test_methods.py | test_supported_methods | 26 | null | |
nerfbaselines/nerfbaselines | import numpy as np
import json
import os
from unittest import mock
import contextlib
import pytest
def _test_generic_dataset(tmp_path, dataset_name, scene, train_size, test_size):
from nerfbaselines.datasets import load_dataset
with contextlib.ExitStack() as stack:
stack.enter_context(mock.patch("nerf... | "nerf" | assert | string_literal | tests/test_datasets.py | test_blender_dataset | 71 | null | |
nerfbaselines/nerfbaselines | import contextlib
import traceback
import sys
import json
import glob
import pprint
import logging
import os
import numpy as np
import click
from PIL import Image
import tempfile
from tqdm import trange
import nerfbaselines
from typing import Type
import urllib.request
from nerfbaselines import (
build_method_class... | None | assert | none_literal | nerfbaselines/cli/_test_method.py | main | 253 | null | |
nerfbaselines/nerfbaselines | import json
import sys
import pytest
from typing import Any, cast
from unittest import mock
from nerfbaselines import get_supported_methods, get_supported_datasets
from nerfbaselines.results import render_markdown_dataset_results_table
def mock_results(results_path, datasets, methods):
from nerfbaselines import ge... | 4 | assert | numeric_literal | tests/test_results.py | test_render_markdown_dataset_results_table | 245 | null | |
nerfbaselines/nerfbaselines | import pytest
import os
import numpy as np
from typing import Optional, TypeVar
from unittest import mock
from unittest.mock import MagicMock
from nerfbaselines import Method, new_cameras
from nerfbaselines import evaluation
from PIL import Image
import tarfile
import zipfile
T = TypeVar("T")
def _assert_not_none(val... | (20, 30) | assert | collection | tests/test_render_frames.py | _verify_folder_single | 316 | null | |
nerfbaselines/nerfbaselines | import contextlib
import sys
import shutil
import json
from typing import cast
from pathlib import Path
import os
import numpy as np
from nerfbaselines import Method, MethodInfo, Cameras, RenderOutput, ModelInfo
from nerfbaselines.utils import Indices
from nerfbaselines.datasets import _colmap_utils as colmap_utils
fro... | [13] | assert | collection | tests/test_train_render.py | test_train_command_extras | 284 | null | |
nerfbaselines/nerfbaselines | import json
import sys
import pytest
from typing import Any, cast
from unittest import mock
from nerfbaselines import get_supported_methods, get_supported_datasets
from nerfbaselines.results import render_markdown_dataset_results_table
def mock_results(results_path, datasets, methods):
from nerfbaselines import ge... | 0 | assert | numeric_literal | tests/test_results.py | assert_compile_dataset_results_correct | 59 | null |
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