80 lines
3.4 KiB
Python
80 lines
3.4 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import numbers
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from collections import namedtuple
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import numpy as np
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import torch
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from pytorch_lightning.utilities.apply_func import apply_to_collection
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def test_recursive_application_to_collection():
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ntc = namedtuple('Foo', ['bar'])
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to_reduce = {
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'a': torch.tensor([1.]), # Tensor
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'b': [torch.tensor([2.])], # list
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'c': (torch.tensor([100.]),), # tuple
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'd': ntc(bar=5.), # named tuple
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'e': np.array([10.]), # numpy array
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'f': 'this_is_a_dummy_str', # string
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'g': 12. # number
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}
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expected_result = {
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'a': torch.tensor([2.]),
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'b': [torch.tensor([4.])],
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'c': (torch.tensor([200.]),),
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'd': ntc(bar=torch.tensor([10.])),
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'e': np.array([20.]),
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'f': 'this_is_a_dummy_str',
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'g': 24.
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}
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reduced = apply_to_collection(to_reduce, (torch.Tensor, numbers.Number, np.ndarray),
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lambda x: x * 2)
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assert isinstance(reduced, dict), ' Type Consistency of dict not preserved'
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assert all([x in reduced for x in to_reduce.keys()]), 'Not all entries of the dict were preserved'
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assert all([isinstance(reduced[k], type(expected_result[k])) for k in to_reduce.keys()]), \
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'At least one type was not correctly preserved'
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assert isinstance(reduced['a'], torch.Tensor), 'Reduction Result of a Tensor should be a Tensor'
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assert torch.allclose(expected_result['a'], reduced['a']), \
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'Reduction of a tensor does not yield the expected value'
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assert isinstance(reduced['b'], list), 'Reduction Result of a list should be a list'
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assert all([torch.allclose(x, y) for x, y in zip(reduced['b'], expected_result['b'])]), \
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'At least one value of list reduction did not come out as expected'
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assert isinstance(reduced['c'], tuple), 'Reduction Result of a tuple should be a tuple'
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assert all([torch.allclose(x, y) for x, y in zip(reduced['c'], expected_result['c'])]), \
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'At least one value of tuple reduction did not come out as expected'
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assert isinstance(reduced['d'], ntc), 'Type Consistency for named tuple not given'
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assert isinstance(reduced['d'].bar, numbers.Number), \
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'Failure in type promotion while reducing fields of named tuples'
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assert reduced['d'].bar == expected_result['d'].bar
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assert isinstance(reduced['e'], np.ndarray), 'Type Promotion in reduction of numpy arrays failed'
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assert reduced['e'] == expected_result['e'], \
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'Reduction of numpy array did not yield the expected result'
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assert isinstance(reduced['f'], str), 'A string should not be reduced'
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assert reduced['f'] == expected_result['f'], 'String not preserved during reduction'
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assert isinstance(reduced['g'], numbers.Number), 'Reduction of a number should result in a tensor'
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assert reduced['g'] == expected_result['g'], 'Reduction of a number did not yield the desired result'
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