blob: ddeea80c560c5ac40839a889c7ed00a7461bd9e7 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
|
# Tensor Transformations
Note: Functions taking `Tensor` arguments can also take anything accepted by
`tf.convert_to_tensor`.
[TOC]
## Casting
TensorFlow provides several operations that you can use to cast tensor data
types in your graph.
* `tf.string_to_number`
* `tf.to_double`
* `tf.to_float`
* `tf.to_bfloat16`
* `tf.to_int32`
* `tf.to_int64`
* `tf.cast`
* `tf.bitcast`
* `tf.saturate_cast`
## Shapes and Shaping
TensorFlow provides several operations that you can use to determine the shape
of a tensor and change the shape of a tensor.
* `tf.broadcast_dynamic_shape`
* `tf.broadcast_static_shape`
* `tf.shape`
* `tf.shape_n`
* `tf.size`
* `tf.rank`
* `tf.reshape`
* `tf.squeeze`
* `tf.expand_dims`
* `tf.meshgrid`
## Slicing and Joining
TensorFlow provides several operations to slice or extract parts of a tensor,
or join multiple tensors together.
* `tf.slice`
* `tf.strided_slice`
* `tf.split`
* `tf.tile`
* `tf.pad`
* `tf.concat`
* `tf.stack`
* `tf.parallel_stack`
* `tf.unstack`
* `tf.reverse_sequence`
* `tf.reverse`
* `tf.reverse_v2`
* `tf.transpose`
* `tf.extract_image_patches`
* `tf.space_to_batch_nd`
* `tf.space_to_batch`
* `tf.required_space_to_batch_paddings`
* `tf.batch_to_space_nd`
* `tf.batch_to_space`
* `tf.space_to_depth`
* `tf.depth_to_space`
* `tf.gather`
* `tf.gather_nd`
* `tf.unique_with_counts`
* `tf.scatter_nd`
* `tf.dynamic_partition`
* `tf.dynamic_stitch`
* `tf.boolean_mask`
* `tf.one_hot`
* `tf.sequence_mask`
* `tf.dequantize`
* `tf.quantize_v2`
* `tf.quantized_concat`
* `tf.setdiff1d`
## Fake quantization
Operations used to help train for better quantization accuracy.
* `tf.fake_quant_with_min_max_args`
* `tf.fake_quant_with_min_max_args_gradient`
* `tf.fake_quant_with_min_max_vars`
* `tf.fake_quant_with_min_max_vars_gradient`
* `tf.fake_quant_with_min_max_vars_per_channel`
* `tf.fake_quant_with_min_max_vars_per_channel_gradient`
|
