Hướng dẫn dùng tensorflow concatenate python

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Used in the notebooks
Used in the notebooks

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Layer that concatenates a list of inputs.

Inherits From: Layer, Module

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.layers.Concatenate

tf.keras.layers.Concatenate(
    axis=-1, **kwargs
)

Used in the notebooks

Used in the guide	Used in the tutorials
Migrate `tf.feature_column`s to Keras preprocessing layers Migrate from TPU embedding_columns to TPUEmbedding layer	Load CSV data pix2pix: Image-to-image translation with a conditional GAN Image segmentation Networks Using text and neural network features

It takes as input a list of tensors, all of the same shape except for the concatenation axis, and returns a single tensor that is the concatenation of all inputs.

x = np.arange(20).reshape(2, 2, 5)
print(x)
[[[ 0  1  2  3  4]
  [ 5  6  7  8  9]]
 [[10 11 12 13 14]
  [15 16 17 18 19]]]
y = np.arange(20, 30).reshape(2, 1, 5)
print(y)
[[[20 21 22 23 24]]
 [[25 26 27 28 29]]]
tf.keras.layers.Concatenate(axis=1)([x, y])

array([[[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [20, 21, 22, 23, 24]],
       [[10, 11, 12, 13, 14],
        [15, 16, 17, 18, 19],
        [25, 26, 27, 28, 29]]])>

x1 = tf.keras.layers.Dense(8)(np.arange(10).reshape(5, 2))
x2 = tf.keras.layers.Dense(8)(np.arange(10, 20).reshape(5, 2))
concatted = tf.keras.layers.Concatenate()([x1, x2])
concatted.shape
TensorShape([5, 16])





Args
 axis
 Axis along which to concatenate.
 **kwargs
 standard layer keyword arguments.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.

Last updated 2022-09-08 UTC.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }] [{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]

 
  Install  
  Learn 

 API 
 Overview  

 Python  

 C++  

 Java  
  More  
  Resources 

 Community 

 Why TensorFlow 

 GitHub 
  Stay organized with collections   Save and categorize content based on your preferences.
Concatenates tensors along one dimension.
View aliases
 Compat aliases for migration



See Migration guide for more details.
tf.compat.v1.concat
tf.concat(
    values, axis, name='concat'
)
Used in the notebooks
Used in the guide Used in the tutorials
Better performance with the tf.data API
Ragged tensors
Customize what happens in Model.fit
Writing a training loop from scratch
TensorFlow basics
word2vec
Simple audio recognition: Recognizing keywords
Learned data compression
Integrated
gradients
Load a pandas DataFrame
See also tf.tile, tf.stack, tf.repeat.
Concatenates the list of tensors values along dimension axis. If values[i].shape = [D0, D1, ... Daxis(i), ...Dn], the concatenated result has shape
[D0, D1, ... Raxis, ...Dn]
where
Raxis = sum(Daxis(i))
That is, the data from the input
tensors is joined along the axis dimension.
The number of dimensions of the input tensors must match, and all dimensions except axis must be equal.
For example:
t1 = [[1, 2, 3], [4, 5, 6]]
t2 = [[7, 8, 9], [10, 11, 12]]
tf.concat([t1, t2], 0)

array([[ 1,  2,  3],
       [ 4,  5,  6],
       [ 7,  8,  9],
       [10, 11, 12]], dtype=int32)>
tf.concat([t1, t2], 1)

array([[ 1,  2,  3,  7,  8,  9],
       [ 4,  5,  6, 10, 11, 12]], dtype=int32)>
As in Python, the axis could also be negative numbers. Negative axis are interpreted as counting from the end of the rank, i.e., axis + rank(values)-th dimension.



For example:
t1 = [[[1, 2], [2, 3]], [[4, 4], [5, 3]]]
t2 = [[[7, 4], [8, 4]], [[2, 10], [15, 11]]]
tf.concat([t1, t2], -1)

  array([[[ 1,  2,  7,  4],
          [ 2,  3,  8,  4]],
         [[ 4,  4,  2, 10],
          [ 5,  3, 15, 11]]], dtype=int32)>
tf.concat([tf.expand_dims(t, axis) for t in tensors], axis)
can be
rewritten as
tf.stack(tensors, axis=axis)

Args
 values
 A list of Tensor objects or a single Tensor.
 axis
 0-D int32 Tensor. Dimension along which to concatenate. Must be in the range [-rank(values), rank(values)). As in Python, indexing for axis is 0-based. Positive axis in the rage of [0, rank(values)) refers to axis-th dimension. And negative axis refers to axis +
rank(values)-th dimension.
 name
 A name for the operation (optional).

Returns
 A Tensor resulting from concatenation of the input tensors.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the
Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2022-09-08 UTC.
 [{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the
information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }] [{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem",
"label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]

programming python Concatenate Keras Tensor Python Tf stack Repeat vector tensorflow np.dot trong python Dataloader tensorflow

Hướng dẫn dùng tensorflow concatenate python

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Used in the notebooks

Args

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Used in the notebooks

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For example:

Args

Returns

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