repo_id stringclasses 400
values | commit_sha stringclasses 400
values | commit_index int32 0 951 | in_repo_split stringclasses 1
value | cross_repo_split stringclasses 1
value | test_file stringlengths 7 121 | test_function stringlengths 1 108 | assertion_type stringclasses 32
values | difficulty stringclasses 8
values | context_lines int32 3 600 | prefix large_stringlengths 44 113k | target large_stringlengths 1 498 | anchor_sha stringclasses 400
values | anchor_index int32 0 951 | qna_source stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/adjacency/test_three_way.py | test_threeway_entropy | assert_* | func_call | 19 | import numpy as np
import torch
from torch.distributions.utils import probs_to_logits
from causica.distributions import ThreeWayAdjacencyDistribution
def test_threeway_entropy():
"""Test entropy is correct for a known distribution"""
num_nodes = 3
logits = torch.nn.Parameter(
torch.zeros(((num_nod... | np.zeros_like(logits.detach().numpy())) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/adjacency/test_three_way.py | test_threeway | assert_* | func_call | 15 | import numpy as np
import torch
from torch.distributions.utils import probs_to_logits
from causica.distributions import ThreeWayAdjacencyDistribution
def test_threeway():
"""Test ThreeWay methods are correct for a known distribution."""
probs = torch.Tensor([[0.4, 0.25, 0.35]])
dist = ThreeWayAdjacencyDis... | np.array([np.log(0.25), np.log(0.4), np.log(0.35)])) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/spline/test_splines.py | test_sample_to_noise | assert_* | variable | 22 | from functools import partial
import torch
from causica.distributions.noise.spline import SplineNoiseModule
INPUT_DIM = 4
torch.manual_seed(123)
assert_close = partial(torch.testing.assert_close, rtol=2e-6, atol=2e-5)
def test_sample_to_noise():
"""Test sample to noise and noise to sample work as expected."""... | recon_samples) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/spline/test_splines.py | test_sample_to_noise | assert_* | func_call | 23 | from functools import partial
import torch
from causica.distributions.noise.spline import SplineNoiseModule
INPUT_DIM = 4
torch.manual_seed(123)
assert_close = partial(torch.testing.assert_close, rtol=2e-6, atol=2e-5)
def test_sample_to_noise():
"""Test sample to noise and noise to sample work as expected."""... | dist.sample_to_noise(recon_samples)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_bernoulli.py | test_sample_to_noise | assert | variable | 48 | import math
import pytest
import torch
import torch.distributions as td
from causica.distributions.noise import BernoulliNoise
def sample_logistic_noise(n_samples, input_dim, base_logits):
"""
Samples a Logistic random variable that can be used to sample this variable.
This method does **not** return har... | eight_sigma | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_bernoulli.py | test_init | assert | func_call | 33 | import math
import pytest
import torch
import torch.distributions as td
from causica.distributions.noise import BernoulliNoise
def sample_logistic_noise(n_samples, input_dim, base_logits):
"""
Samples a Logistic random variable that can be used to sample this variable.
This method does **not** return har... | torch.Size([3]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_bernoulli.py | test_init | assert | func_call | 40 | import math
import pytest
import torch
import torch.distributions as td
from causica.distributions.noise import BernoulliNoise
def sample_logistic_noise(n_samples, input_dim, base_logits):
"""
Samples a Logistic random variable that can be used to sample this variable.
This method does **not** return har... | torch.Size([2, 3]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_bernoulli.py | test_init | assert_* | func_call | 41 | import math
import pytest
import torch
import torch.distributions as td
from causica.distributions.noise import BernoulliNoise
def sample_logistic_noise(n_samples, input_dim, base_logits):
"""
Samples a Logistic random variable that can be used to sample this variable.
This method does **not** return har... | torch.Tensor([[0.6, 0.4, 0.2], [0.7, 0.7, 0.7]])) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_categorical.py | test_noise_reconstruction | assert | variable | 36 | import math
import pytest
import torch
from causica.distributions.noise import CategoricalNoise
@pytest.mark.parametrize(
"base_logits,x_hat",
[
(0.0, torch.tensor([0.0, 0.0, 0.0])),
(1.0, torch.tensor([0.0, 0.0, 0.0])),
(0.0, torch.tensor([0.1, 0.5, 1.0])),
(1.0, torch.tensor... | eight_sigma | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_categorical.py | test_init | assert | func_call | 16 | import math
import pytest
import torch
from causica.distributions.noise import CategoricalNoise
def test_init():
base_logits = torch.Tensor([0.3, 0.2, 0.1])
# no batch
x_hat = torch.Tensor([0.3, 0.2, 0.1])
noise_model = CategoricalNoise(x_hat, base_logits)
assert noise_model.logits.shape == | torch.Size([3]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_categorical.py | test_init | assert | func_call | 24 | import math
import pytest
import torch
from causica.distributions.noise import CategoricalNoise
def test_init():
base_logits = torch.Tensor([0.3, 0.2, 0.1])
# no batch
x_hat = torch.Tensor([0.3, 0.2, 0.1])
noise_model = CategoricalNoise(x_hat, base_logits)
assert noise_model.logits.shape == tor... | torch.Size([2, 3]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_passthrough | assert_* | complex_expr | 33 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise.mode) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_passthrough | assert_* | complex_expr | 34 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise.mean) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_properties | assert_* | complex_expr | 34 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise_a.mode) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_properties | assert_* | complex_expr | 35 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise_b.mode) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_properties | assert_* | complex_expr | 36 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise_a.mean) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_properties | assert_* | complex_expr | 37 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise_b.mean) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_passthrough | assert_* | func_call | 32 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise.entropy()) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_empirical | assert | complex_expr | 43 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | joint_log_probs.shape | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_empirical | assert_* | func_call | 55 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | std(joint_log_probs)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_empirical | assert_* | func_call | 54 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | mean(joint_log_probs)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_empirical | assert | func_call | 41 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | joint_samples.get("a").shape | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_empirical | assert | func_call | 42 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | joint_samples.get("b").shape | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_properties | assert_* | func_call | 33 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise_a.entropy() + noise_b.entropy()) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_joint.py | test_joint_noise_sample_log_prob | assert_* | func_call | 35 | import pytest
import torch
from tensordict import TensorDict
from causica.distributions import (
BernoulliNoise,
CategoricalNoise,
IndependentNoise,
JointNoise,
Noise,
UnivariateNormalNoise,
)
torch.manual_seed(0)
NOISE_DISTRIBUTIONS = [
IndependentNoise(BernoulliNoise(torch.randn(3), tor... | noise_a.log_prob(sample_a) + noise_b.log_prob(sample_b)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/noise/test_univariate_normal.py | test_init | assert | collection | 12 | import pytest
import torch
from causica.distributions.noise import UnivariateNormalNoise
@pytest.mark.parametrize(("batch", "dimension"), [(1, 10), (2, 5)])
def test_init(batch, dimension):
mean = torch.randn((batch, dimension))
scale = torch.ones((batch, dimension))
noise_model = UnivariateNormalNoise(lo... | (batch, dimension) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/test_sem_distribution.py | test_sem_distribution_passthrough | assert_* | func_call | 33 | import pytest
import torch
from causica.distributions.adjacency.adjacency_distributions import AdjacencyDistribution
from causica.distributions.adjacency.enco import ENCOAdjacencyDistribution
from causica.distributions.noise.joint import JointNoiseModule
from causica.distributions.noise.noise import Noise, NoiseModule... | sem_dist.entropy()) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/test_sem_distribution.py | test_sem_distribution_samples | assert | func_call | 33 | import pytest
import torch
from causica.distributions.adjacency.adjacency_distributions import AdjacencyDistribution
from causica.distributions.adjacency.enco import ENCOAdjacencyDistribution
from causica.distributions.noise.joint import JointNoiseModule
from causica.distributions.noise.noise import Noise, NoiseModule... | sample_shape.numel() | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/test_sem_distribution.py | test_sem_distribution_passthrough | assert_* | complex_expr | 34 | import pytest
import torch
from causica.distributions.adjacency.adjacency_distributions import AdjacencyDistribution
from causica.distributions.adjacency.enco import ENCOAdjacencyDistribution
from causica.distributions.noise.joint import JointNoiseModule
from causica.distributions.noise.noise import Noise, NoiseModule... | sem_dist.mean.graph) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/test_sem_distribution.py | test_sem_distribution_passthrough | assert_* | complex_expr | 35 | import pytest
import torch
from causica.distributions.adjacency.adjacency_distributions import AdjacencyDistribution
from causica.distributions.adjacency.enco import ENCOAdjacencyDistribution
from causica.distributions.noise.joint import JointNoiseModule
from causica.distributions.noise.noise import Noise, NoiseModule... | sem_dist.mode.graph) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/test_sem_distribution.py | test_sem_distribution_passthrough | assert_* | func_call | 36 | import pytest
import torch
from causica.distributions.adjacency.adjacency_distributions import AdjacencyDistribution
from causica.distributions.adjacency.enco import ENCOAdjacencyDistribution
from causica.distributions.noise.joint import JointNoiseModule
from causica.distributions.noise.noise import Noise, NoiseModule... | sem_dist.log_prob(sem_dist.mode)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_base.py | test_typed_transform | assert | variable | 16 | import gc
from causica.distributions.transforms.base import TypedTransform
def test_typed_transform() -> None:
"""Tests the basic functionality of TypedTransform.
Should be paired with a mypy step to ensure that the types are consistent."""
transform = _StrIntTransform()
x: str = "1"
y: int = tr... | x | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_base.py | test_weak_ref_inv_release | assert | variable | 13 | import gc
from causica.distributions.transforms.base import TypedTransform
def test_weak_ref_inv_release() -> None:
"""Test that the weak reference to the inverse is released."""
transform = _StrIntTransform()
inverse = transform.inv
id_ = id(inverse)
# Check that the inverse is kept while there ... | id_ | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_transform_module_output | assert_* | variable | 33 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | data) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_transform_module_registration_buffers | assert_* | variable | 31 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | offset) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_sequential_transform_module_inner_buffers | assert_* | variable | 33 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | buffer) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_transform_module_output | assert | variable | 32 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | transform | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_transform_module_output | assert_* | variable | 29 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | expected_result) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_registration | assert_* | complex_expr | 48 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | state_dict[name]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_registration | assert_* | func_call | 65 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | y.to(**to_kwargs)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_registration | assert | func_call | 37 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | set(tensors_modified) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_registration | assert_* | complex_expr | 39 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | tensors_modified[name]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/distributions/transforms/test_transform_modules.py | test_registration | assert_* | func_call | 62 | import io
import itertools
from typing import Any, TypeVar
import pytest
import torch
from tensordict import TensorDictBase, make_tensordict
from causica.distributions.transforms import SequentialTransformModule
from causica.distributions.transforms.base import TransformModule
from causica.distributions.transforms.jo... | y.get(key).to(**to_kwargs)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_do_functional_relationships.py | test_linear_3d_graph_do_1_node | assert | collection | 26 | import pytest
import torch
from tensordict import TensorDict
from causica.functional_relationships import LinearFunctionalRelationships, create_do_functional_relationship
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_three_variable_dict():
return {"x1": to... | (100, 2) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_do_functional_relationships.py | test_linear_3d_graph_do_1_node | assert | collection | 27 | import pytest
import torch
from tensordict import TensorDict
from causica.functional_relationships import LinearFunctionalRelationships, create_do_functional_relationship
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_three_variable_dict():
return {"x1": to... | (100, 1) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_do_functional_relationships.py | test_do_linear_graph_stack | assert | collection | 22 | import pytest
import torch
from tensordict import TensorDict
from causica.functional_relationships import LinearFunctionalRelationships, create_do_functional_relationship
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_three_variable_dict():
return {"x1": to... | (100, 2, 1) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_functional_relationships.py | test_func_rel_init | assert | numeric_literal | 28 | import math
import pytest
import torch
from causica.functional_relationships import (
DECIEmbedFunctionalRelationships,
LinearFunctionalRelationships,
RFFFunctionalRelationships,
)
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_two_variable_sample(... | 3 | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_functional_relationships.py | test_func_rel_forward | assert | collection | 30 | import math
import pytest
import torch
from causica.functional_relationships import (
DECIEmbedFunctionalRelationships,
LinearFunctionalRelationships,
RFFFunctionalRelationships,
)
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_two_variable_sample(... | (3, 1) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_functional_relationships.py | test_func_rel_forward | assert | collection | 31 | import math
import pytest
import torch
from causica.functional_relationships import (
DECIEmbedFunctionalRelationships,
LinearFunctionalRelationships,
RFFFunctionalRelationships,
)
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_two_variable_sample(... | (3, 2) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_functional_relationships.py | test_func_rel_forward_multigraph | assert | collection | 30 | import math
import pytest
import torch
from causica.functional_relationships import (
DECIEmbedFunctionalRelationships,
LinearFunctionalRelationships,
RFFFunctionalRelationships,
)
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_two_variable_sample(... | (3, 2, 1) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_functional_relationships.py | test_func_rel_forward_multigraph | assert | collection | 31 | import math
import pytest
import torch
from causica.functional_relationships import (
DECIEmbedFunctionalRelationships,
LinearFunctionalRelationships,
RFFFunctionalRelationships,
)
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_two_variable_sample(... | (3, 2, 2) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/functional_relationships/test_functional_relationships.py | test_func_rel_forward | assert | collection | 29 | import math
import pytest
import torch
from causica.functional_relationships import (
DECIEmbedFunctionalRelationships,
LinearFunctionalRelationships,
RFFFunctionalRelationships,
)
def fixture_two_variable_dict():
return {"x1": torch.Size([1]), "x2": torch.Size([2])}
def fixture_two_variable_sample(... | {"x1", "x2"} | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_evaluation.py | test_evaluation_ate | assert | func_call | 42 | import os
import pytest
import torch
from tensordict import TensorDict
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
from causica.datasets.variable_types import VariableTypeEnum
from causica.distributions ... | tuple() | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_evaluation.py | test_evaluation_interventional_likelihood | assert | func_call | 44 | import os
import pytest
import torch
from tensordict import TensorDict
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
from causica.datasets.variable_types import VariableTypeEnum
from causica.distributions ... | torch.Size([data[0][0].intervention_data.shape[0] * 2]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_csuite | assert | variable | 23 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
@pytest.mark.parametrize("dataset", ["csuite_weak_arrows", "csuite_linexp_2"])
def test_load_csuite(dataset):
"""Test that we can ... | int_groups_a | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_csuite | assert | variable | 24 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
@pytest.mark.parametrize("dataset", ["csuite_weak_arrows", "csuite_linexp_2"])
def test_load_csuite(dataset):
"""Test that we can ... | int_groups_b | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_csuite | assert | collection | 31 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
@pytest.mark.parametrize("dataset", ["csuite_weak_arrows", "csuite_linexp_2"])
def test_load_csuite(dataset):
"""Test that we can ... | (num_nodes, num_nodes) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_csuite | assert | func_call | 18 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
@pytest.mark.parametrize("dataset", ["csuite_weak_arrows", "csuite_linexp_2"])
def test_load_csuite(dataset):
"""Test that we can ... | tensordict_shapes(test_data) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_counterfactuals | assert | complex_expr | 27 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
def test_load_counterfactuals():
dataset = "csuite_linexp_2"
root_path = os.path.join(CAUSICA_DATASETS_PATH, dataset)
# no... | intervention_a.counterfactual_data.batch_size | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_counterfactuals | assert | complex_expr | 28 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
def test_load_counterfactuals():
dataset = "csuite_linexp_2"
root_path = os.path.join(CAUSICA_DATASETS_PATH, dataset)
# no... | intervention_b.counterfactual_data.batch_size | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_counterfactuals | assert | func_call | 23 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
def test_load_counterfactuals():
dataset = "csuite_linexp_2"
root_path = os.path.join(CAUSICA_DATASETS_PATH, dataset)
# no... | tensordict_shapes(intervention_a.factual_data) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_counterfactuals | assert | func_call | 24 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
def test_load_counterfactuals():
dataset = "csuite_linexp_2"
root_path = os.path.join(CAUSICA_DATASETS_PATH, dataset)
# no... | tensordict_shapes(intervention_b.factual_data) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_load_csuite.py | test_load_csuite | assert | func_call | 25 | import os
import pytest
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data
from causica.datasets.tensordict_utils import tensordict_shapes
@pytest.mark.parametrize("dataset", ["csuite_weak_arrows", "csuite_linexp_2"])
def test_load_csuite(dataset):
"""Test that we can ... | tensordict_shapes( intervention_b.intervention_data ) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_pytorch_lightning.py | test_pytorch_lightning_save_checkpoint | assert_* | complex_expr | 58 | import mlflow
import numpy as np
import pytest
import pytorch_lightning as pl
import torch
from causica.distributions import ExpertGraphContainer
from causica.distributions.noise.joint import ContinuousNoiseDist
from causica.lightning.data_modules.variable_spec_data import CSuiteDataModule
from causica.lightning.modul... | module2_params[key]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_pytorch_lightning.py | test_pytorch_lightning_save_checkpoint | assert | func_call | 55 | import mlflow
import numpy as np
import pytest
import pytorch_lightning as pl
import torch
from causica.distributions import ExpertGraphContainer
from causica.distributions.noise.joint import ContinuousNoiseDist
from causica.lightning.data_modules.variable_spec_data import CSuiteDataModule
from causica.lightning.modul... | module2_params.keys() | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_pytorch_lightning.py | test_pytorch_lightning_save_checkpoint | assert | func_call | 61 | import mlflow
import numpy as np
import pytest
import pytorch_lightning as pl
import torch
from causica.distributions import ExpertGraphContainer
from causica.distributions.noise.joint import ContinuousNoiseDist
from causica.lightning.data_modules.variable_spec_data import CSuiteDataModule
from causica.lightning.modul... | module1_params.keys() | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_pytorch_lightning.py | test_pytorch_lightning_save_checkpoint | assert_* | complex_expr | 63 | import mlflow
import numpy as np
import pytest
import pytorch_lightning as pl
import torch
from causica.distributions import ExpertGraphContainer
from causica.distributions.noise.joint import ContinuousNoiseDist
from causica.lightning.data_modules.variable_spec_data import CSuiteDataModule
from causica.lightning.modul... | module2.constraint_matrix) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_pytorch_lightning.py | test_pytorch_lightning_deterministic | assert_* | func_call | 43 | import mlflow
import numpy as np
import pytest
import pytorch_lightning as pl
import torch
from causica.distributions import ExpertGraphContainer
from causica.distributions.noise.joint import ContinuousNoiseDist
from causica.lightning.data_modules.variable_spec_data import CSuiteDataModule
from causica.lightning.modul... | _module_to_parameter(module2)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_pytorch_lightning.py | test_pytorch_lightning_expert_input | assert_* | func_call | 46 | import mlflow
import numpy as np
import pytest
import pytorch_lightning as pl
import torch
from causica.distributions import ExpertGraphContainer
from causica.distributions.noise.joint import ContinuousNoiseDist
from causica.lightning.data_modules.variable_spec_data import CSuiteDataModule
from causica.lightning.modul... | expert_graph_container.dag.to(dtype=torch.float32)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_counterfactuals | assert | complex_expr | 73 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | cf_2[2] | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_csuite | assert_* | variable | 70 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | adj_mat_2) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | _load_and_test_dataset | assert | variable | 22 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | int_groups_a | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | _load_and_test_dataset | assert | variable | 23 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | int_groups_b | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_csuite | assert_* | variable | 71 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | train_data_2) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_csuite | assert | complex_expr | 79 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | intervention_2[2] | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_csuite | assert | variable | 69 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | variables_metadata_2 | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_csuite | assert | func_call | 74 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | len(interventions_2) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | _load_and_test_dataset | assert | collection | 30 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | (num_nodes, num_nodes) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_counterfactuals | assert | func_call | 68 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | len(counterfactuals_2) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_counterfactuals | assert_* | func_call | 71 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | getattr(cf_2[0], field)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | test_load_save_counterfactuals | assert_* | func_call | 72 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | getattr(cf_2[1], field)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | _load_and_test_dataset | assert | func_call | 16 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | tensordict_shapes(test_data) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | load_and_test_counterfactuals | assert | complex_expr | 51 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | intervention_a.counterfactual_data.batch_size | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | load_and_test_counterfactuals | assert | complex_expr | 52 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | intervention_b.counterfactual_data.batch_size | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | load_and_test_counterfactuals | assert | func_call | 47 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | tensordict_shapes(intervention_a.factual_data) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | load_and_test_counterfactuals | assert | func_call | 48 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | tensordict_shapes(intervention_b.factual_data) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/integration/test_save_load_csuite.py | _load_and_test_dataset | assert | func_call | 24 | import os
import tempfile
import pytest
import torch
from causica.datasets.causica_dataset_format import CAUSICA_DATASETS_PATH, DataEnum, load_data, save_data, save_dataset
from causica.datasets.tensordict_utils import tensordict_shapes
def _load_and_test_dataset(root_path: str):
variables_metadata = load_data(r... | tensordict_shapes( intervention_b.intervention_data ) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_basic_data_module.py | test_basic_data_module | assert | func_call | 90 | import pandas as pd
import torch
from causica.datasets.causica_dataset_format import Variable
from causica.lightning.data_modules.basic_data_module import BasicDECIDataModule
def test_basic_data_module():
"""Test Basic Data Module functionality"""
df = pd.DataFrame(
{
"x0_0": {
... | torch.Size([2]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_basic_data_module.py | test_basic_data_module | assert | func_call | 91 | import pandas as pd
import torch
from causica.datasets.causica_dataset_format import Variable
from causica.lightning.data_modules.basic_data_module import BasicDECIDataModule
def test_basic_data_module():
"""Test Basic Data Module functionality"""
df = pd.DataFrame(
{
"x0_0": {
... | torch.Size([10]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_basic_data_module.py | test_basic_data_module | assert | func_call | 92 | import pandas as pd
import torch
from causica.datasets.causica_dataset_format import Variable
from causica.lightning.data_modules.basic_data_module import BasicDECIDataModule
def test_basic_data_module():
"""Test Basic Data Module functionality"""
df = pd.DataFrame(
{
"x0_0": {
... | torch.Size([10, 2]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_callbacks.py | test_mlflow_save_config_callback | assert | func_call | 35 | import os
from pathlib import Path
import mlflow
import pytest
import yaml
from jsonargparse import Namespace
from mlflow import ActiveRun
from pytorch_lightning import LightningModule, Trainer
from pytorch_lightning.cli import LightningArgumentParser
from pytorch_lightning.trainer.states import TrainerFn
from causic... | namespace.as_dict() | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_loggers.py | test_buffering_mlflow_logger | assert | numeric_literal | 16 | from pathlib import Path
import mlflow
from causica.lightning.loggers import BufferingMlFlowLogger
def test_buffering_mlflow_logger(tmp_path: Path):
mlflow.set_tracking_uri(tmp_path)
client = mlflow.tracking.MlflowClient(tracking_uri=str(tmp_path))
experiment_id = client.create_experiment("test")
run... | 2 | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_loggers.py | test_buffering_mlflow_logger | assert | numeric_literal | 18 | from pathlib import Path
import mlflow
from causica.lightning.loggers import BufferingMlFlowLogger
def test_buffering_mlflow_logger(tmp_path: Path):
mlflow.set_tracking_uri(tmp_path)
client = mlflow.tracking.MlflowClient(tracking_uri=str(tmp_path))
experiment_id = client.create_experiment("test")
run... | 0 | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_loggers.py | test_buffering_mlflow_logger | assert | numeric_literal | 20 | from pathlib import Path
import mlflow
from causica.lightning.loggers import BufferingMlFlowLogger
def test_buffering_mlflow_logger(tmp_path: Path):
mlflow.set_tracking_uri(tmp_path)
client = mlflow.tracking.MlflowClient(tracking_uri=str(tmp_path))
experiment_id = client.create_experiment("test")
run... | 1 | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_variable_spec_data.py | test_variable_spec_data | assert | func_call | 137 | import json
import numpy as np
import pandas as pd
import pytest
import torch
from causica.datasets.causica_dataset_format import Variable, VariablesMetadata
from causica.lightning.data_modules.variable_spec_data import VariableSpecDataModule
DF = pd.DataFrame(
{
"x0_0": {
0: -0.5569139122962... | torch.Size([2]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_variable_spec_data.py | test_variable_spec_data | assert_* | func_call | 142 | import json
import numpy as np
import pandas as pd
import pytest
import torch
from causica.datasets.causica_dataset_format import Variable, VariablesMetadata
from causica.lightning.data_modules.variable_spec_data import VariableSpecDataModule
DF = pd.DataFrame(
{
"x0_0": {
0: -0.5569139122962... | torch.zeros(2)) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_variable_spec_data.py | test_variable_spec_data | assert | func_call | 138 | import json
import numpy as np
import pandas as pd
import pytest
import torch
from causica.datasets.causica_dataset_format import Variable, VariablesMetadata
from causica.lightning.data_modules.variable_spec_data import VariableSpecDataModule
DF = pd.DataFrame(
{
"x0_0": {
0: -0.5569139122962... | torch.Size([10]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/lightning/test_variable_spec_data.py | test_variable_spec_data | assert | func_call | 139 | import json
import numpy as np
import pandas as pd
import pytest
import torch
from causica.datasets.causica_dataset_format import Variable, VariablesMetadata
from causica.lightning.data_modules.variable_spec_data import VariableSpecDataModule
DF = pd.DataFrame(
{
"x0_0": {
0: -0.5569139122962... | torch.Size([10, 2]) | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/metrics/test_graph_eval_metrics.py | test_graph_eval_metrics | assert | complex_expr | 87 | import pytest
import torch
from causica.graph.evaluation_metrics import (
adjacency_f1,
adjacency_precision_recall,
orientation_f1,
orientation_precision_recall,
)
MATRICES = [
torch.tensor([[0, 1, 1], [0, 0, 0], [0, 0, 0]]),
torch.tensor([[0, 0, 0], [1, 0, 0], [1, 0, 0]]),
torch.tensor([[... | adj_metrics["adjacency_fscore"] | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
microsoft/causica | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | train | train | test/metrics/test_graph_eval_metrics.py | test_graph_eval_metrics | assert | complex_expr | 82 | import pytest
import torch
from causica.graph.evaluation_metrics import (
adjacency_f1,
adjacency_precision_recall,
orientation_f1,
orientation_precision_recall,
)
MATRICES = [
torch.tensor([[0, 1, 1], [0, 0, 0], [0, 0, 0]]),
torch.tensor([[0, 0, 0], [1, 0, 0], [1, 0, 0]]),
torch.tensor([[... | orientation_metrics["orientation_fscore"] | f20772bf4e2d104aea043f66226b35d2527640f9 | 15 | v2_extractor_at_anchor |
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