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Fix test failures caused by warns(None). #1200

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Fix test failures caused by warns(None). #1200

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13 changes: 5 additions & 8 deletions tests/nn/pipe/test_pipe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
from collections import OrderedDict
from copy import deepcopy
import time
import warnings

import pytest
import torch
Expand Down Expand Up @@ -123,23 +124,19 @@ def test_batch_size_indivisible():
model = nn.Sequential(nn.Linear(1, 1))
model = Pipe(model, balance=[1], devices=["cpu"], chunks=4)

with pytest.warns(None) as record:
with warnings.catch_warnings(action="error"):
# Indivisible batch size is legal.
model(torch.rand(7, 1))

# Indivisible batch size is legal.
assert not record


def test_batch_size_small():
model = nn.Sequential(nn.Linear(1, 1))
model = Pipe(model, balance=[1], devices=["cpu"], chunks=4)

with pytest.warns(None) as record:
with warnings.catch_warnings(action="error"):
# Batch size smaller than chunks is legal.
model(torch.rand(2, 1))

# Batch size smaller than chunks is legal.
assert not record


def test_checkpoint_mode():
def count_grad_fn(grad_fn, name, visited=set()):
Expand Down
13 changes: 5 additions & 8 deletions tests/nn/pipe_process/test_pipe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@
from copy import deepcopy
import os
import time
import warnings

import pytest
import torch
Expand Down Expand Up @@ -222,25 +223,21 @@ def batch_size_indivisible(pipe_class):
model = nn.Sequential(nn.Linear(1, 1))
model = pipe_class(model, balance=[1], worker_map=get_worker_map(), chunks=4)

with pytest.warns(None) as record:
with warnings.catch_warnings(action="error"):
# Indivisible batch size is legal.
model(torch.rand(7, 1))

# Indivisible batch size is legal.
assert not record


@torch_spawn([1])
@pytest.mark.parametrize("pipe_class", [AsyncPipe])
def batch_size_small(pipe_class):
model = nn.Sequential(nn.Linear(1, 1))
model = pipe_class(model, balance=[1], worker_map=get_worker_map(), chunks=4)

with pytest.warns(None) as record:
with warnings.catch_warnings(action="error"):
# Batch size smaller than chunks is legal.
model(torch.rand(2, 1))

# Batch size smaller than chunks is legal.
assert not record


@torch_spawn([1])
@pytest.mark.parametrize("pipe_class", [AsyncPipe])
Expand Down