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69 lines
2.6 KiB
69 lines
2.6 KiB
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. |
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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 random |
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import paddle |
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class ImagePool(): |
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"""This class implements an image buffer that stores previously generated images. |
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This buffer enables us to update discriminators using a history of generated images |
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rather than the ones produced by the latest generators. |
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Args: |
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pool_size (int) -- the size of image buffer, if pool_size=0, no buffer will be created |
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""" |
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def __init__(self, pool_size, prob=0.5): |
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self.pool_size = pool_size |
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self.prob = prob |
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if self.pool_size > 0: |
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self.num_imgs = 0 |
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self.images = [] |
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def query(self, images): |
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"""Return an image from the pool. |
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Args: |
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images (paddle.Tensor): the latest generated images from the generator |
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Returns images from the buffer. |
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""" |
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# if the buffer size is 0, do nothing |
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if self.pool_size == 0: |
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return images |
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return_images = [] |
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for image in images: |
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image = paddle.unsqueeze(image, 0) |
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# if the buffer is not full; keep inserting current images to the buffer |
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if self.num_imgs < self.pool_size: |
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self.num_imgs = self.num_imgs + 1 |
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self.images.append(image) |
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return_images.append(image) |
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else: |
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p = random.uniform(0, 1) |
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# by 50% chance, the buffer will return a previously stored image, and insert the current image into the buffer |
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if p > self.prob: |
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random_id = random.randint(0, self.pool_size - 1) |
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tmp = self.images[random_id].clone() |
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self.images[random_id] = image |
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return_images.append(tmp) |
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else: |
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# by another 50% chance, the buffer will return the current image |
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return_images.append(image) |
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# collect all the images and return |
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return_images = paddle.concat(return_images, 0) |
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return return_images
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