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Source code for flash.core.data.batch

# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any, Callable, List, TYPE_CHECKING

from torch import nn, Tensor

from flash.core.data.utilities.classification import _is_list_like

if TYPE_CHECKING:
    from flash.core.data.io.input import ServeInput


class _ServeInputProcessor(nn.Module):
    def __init__(
        self,
        serve_input: "ServeInput",
        collate_fn: Callable,
    ):
        super().__init__()
        self.serve_input = serve_input
        self.collate_fn = collate_fn

    def forward(self, sample: str):
        sample = self.serve_input._call_load_sample(sample)
        if not isinstance(sample, list):
            sample = [sample]
        sample = self.collate_fn(sample)
        return sample


def _is_list_like_excluding_str(x):
    return _is_list_like(x) and str(x) != x


[docs]def default_uncollate(batch: Any) -> List[Any]: """This function is used to uncollate a batch into samples. The following conditions are used: - if the ``batch`` is a ``dict``, the result will be a list of dicts - if the ``batch`` is list-like, the result is guaranteed to be a list Args: batch: The batch of outputs to be uncollated. Returns: The uncollated list of predictions. Raises: ValueError: If the input is a ``dict`` whose values are not all list-like. ValueError: If the input is a ``dict`` whose values are not all the same length. ValueError: If the input is not a ``dict`` or list-like. """ if isinstance(batch, dict): if any(not _is_list_like_excluding_str(sub_batch) for sub_batch in batch.values()): raise ValueError("When uncollating a dict, all sub-batches (values) are expected to be list-like.") if len({len(sub_batch) for sub_batch in batch.values()}) > 1: raise ValueError("When uncollating a dict, all sub-batches (values) are expected to have the same length.") elements = [default_uncollate(element) for element in zip(*batch.values())] return [dict(zip(batch.keys(), element)) for element in elements] if isinstance(batch, (list, tuple, Tensor)): return list(batch) raise ValueError( "The batch of outputs to be uncollated is expected to be a `dict` or list-like " f"(e.g. `Tensor`, `list`, `tuple`, etc.), but got input of type: {type(batch)}" )

© Copyright 2020-2021, PyTorch Lightning. Revision da42a635.

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