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80b01ba4f3
Summary: cc orionr sanekmelnikov Pull Request resolved: https://github.com/pytorch/pytorch/pull/36496 Differential Revision: D21012775 Pulled By: natalialunova fbshipit-source-id: 2dc978d70d457b511bd13a3399246ae0349ff8ca
71 lines
2.8 KiB
Python
71 lines
2.8 KiB
Python
import math
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import numpy as np
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from ._convert_np import make_np
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from ._utils import make_grid
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from tensorboard.compat import tf
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from tensorboard.plugins.projector.projector_config_pb2 import EmbeddingInfo
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def make_tsv(metadata, save_path, metadata_header=None):
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if not metadata_header:
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metadata = [str(x) for x in metadata]
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else:
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assert len(metadata_header) == len(metadata[0]), \
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'len of header must be equal to the number of columns in metadata'
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metadata = ['\t'.join(str(e) for e in l)
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for l in [metadata_header] + metadata]
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metadata_bytes = tf.compat.as_bytes('\n'.join(metadata) + '\n')
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fs = tf.io.gfile.get_filesystem(save_path)
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fs.write(fs.join(save_path, 'metadata.tsv'), metadata_bytes, binary_mode=True)
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# https://github.com/tensorflow/tensorboard/issues/44 image label will be squared
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def make_sprite(label_img, save_path):
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from PIL import Image
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from io import BytesIO
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# this ensures the sprite image has correct dimension as described in
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# https://www.tensorflow.org/get_started/embedding_viz
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nrow = int(math.ceil((label_img.size(0)) ** 0.5))
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arranged_img_CHW = make_grid(make_np(label_img), ncols=nrow)
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# augment images so that #images equals nrow*nrow
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arranged_augment_square_HWC = np.zeros((arranged_img_CHW.shape[2], arranged_img_CHW.shape[2], 3))
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arranged_img_HWC = arranged_img_CHW.transpose(1, 2, 0) # chw -> hwc
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arranged_augment_square_HWC[:arranged_img_HWC.shape[0], :, :] = arranged_img_HWC
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im = Image.fromarray(np.uint8((arranged_augment_square_HWC * 255).clip(0, 255)))
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with BytesIO() as buf:
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im.save(buf, format="PNG")
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im_bytes = buf.getvalue()
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fs = tf.io.gfile.get_filesystem(save_path)
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fs.write(fs.join(save_path, 'sprite.png'), im_bytes, binary_mode=True)
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def get_embedding_info(metadata, label_img, filesys, subdir, global_step, tag):
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info = EmbeddingInfo()
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info.tensor_name = "{}:{}".format(tag, str(global_step).zfill(5))
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info.tensor_path = filesys.join(subdir, 'tensors.tsv')
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if metadata is not None:
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info.metadata_path = filesys.join(subdir, 'metadata.tsv')
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if label_img is not None:
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info.sprite.image_path = filesys.join(subdir, 'sprite.png')
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info.sprite.single_image_dim.extend([label_img.size(3), label_img.size(2)])
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return info
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def write_pbtxt(save_path, contents):
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fs = tf.io.gfile.get_filesystem(save_path)
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config_path = fs.join(save_path, 'projector_config.pbtxt')
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fs.write(config_path, tf.compat.as_bytes(contents), binary_mode=True)
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def make_mat(matlist, save_path):
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fs = tf.io.gfile.get_filesystem(save_path)
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with tf.io.gfile.GFile(fs.join(save_path, 'tensors.tsv'), 'wb') as f:
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for x in matlist:
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x = [str(i.item()) for i in x]
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f.write(tf.compat.as_bytes('\t'.join(x) + '\n'))
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