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Function _extract_images

neural_network/input_data.py:47–72  ·  view source on GitHub ↗

Extract the images into a 4D uint8 numpy array [index, y, x, depth]. Args: f: A file object that can be passed into a gzip reader. Returns: data: A 4D uint8 numpy array [index, y, x, depth]. Raises: ValueError: If the bytestream does not start with 2051.

(f)

Source from the content-addressed store, hash-verified

45
46@deprecated(None, "Please use tf.data to implement this functionality.")
47def _extract_images(f):
48 """Extract the images into a 4D uint8 numpy array [index, y, x, depth].
49
50 Args:
51 f: A file object that can be passed into a gzip reader.
52
53 Returns:
54 data: A 4D uint8 numpy array [index, y, x, depth].
55
56 Raises:
57 ValueError: If the bytestream does not start with 2051.
58
59 """
60 print("Extracting", f.name)
61 with gzip.GzipFile(fileobj=f) as bytestream:
62 magic = _read32(bytestream)
63 if magic != 2051:
64 msg = f"Invalid magic number {magic} in MNIST image file: {f.name}"
65 raise ValueError(msg)
66 num_images = _read32(bytestream)
67 rows = _read32(bytestream)
68 cols = _read32(bytestream)
69 buf = bytestream.read(rows * cols * num_images)
70 data = np.frombuffer(buf, dtype=np.uint8)
71 data = data.reshape(num_images, rows, cols, 1)
72 return data
73
74
75@deprecated(None, "Please use tf.one_hot on tensors.")

Callers 1

read_data_setsFunction · 0.85

Calls 1

_read32Function · 0.85

Tested by

no test coverage detected