模块“tensorflow.compat.v1”没有属性“contrib”

Question

由于 tensorflow 2 不支持“占位符”功能，我必须按以下方式导入 tensorflow：

import tensorflow.compat.v1 as tf

tf.disable_v2_behavior() 

进一步的代码片段在下面的 co 中使用了 'contrib' 函数

def encoding_layer(rnn_size, sequence_length, num_layers, rnn_inputs, keep_prob):
    '''Create the encoding layer'''
    
    for layer in range(num_layers):
        with tf.variable_scope('encoder_{}'.format(layer)):
            cell_fw = tf.contrib.rnn.LSTMCell(rnn_size,
                                              initializer=tf.random_uniform_initializer(-0.1, 0.1, seed=2))
            cell_fw = tf.contrib.rnn.DropoutWrapper(cell_fw, 
                                                    input_keep_prob = keep_prob)

            cell_bw = tf.contrib.rnn.LSTMCell(rnn_size,
                                              initializer=tf.random_uniform_initializer(-0.1, 0.1, seed=2))
            cell_bw = tf.contrib.rnn.DropoutWrapper(cell_bw, 
                                                    input_keep_prob = keep_prob)

            enc_output, enc_state = tf.nn.bidirectional_dynamic_rnn(cell_fw, 
                                                                    cell_bw, 
                                                                    rnn_inputs,
                                                                    sequence_length,
                                                                    dtype=tf.float32)
    # Join outputs since we are using a bidirectional RNN
    enc_output = tf.concat(enc_output,2)
    
    return enc_output, enc_state

最后的代码块是：

# Build the graph
train_graph = tf.Graph()
# Set the graph to default to ensure that it is ready for training
with train_graph.as_default():
    
    # Load the model inputs    
    input_data, targets, lr, keep_prob, summary_length, max_summary_length, text_length = model_inputs()

    # Create the training and inference logits
    training_logits, inference_logits = seq2seq_model(tf.reverse(input_data, [-1]),
                                                      targets, 
                                                      keep_prob,   
                                                      text_length,
                                                      summary_length,
                                                      max_summary_length,
                                                      len(vocab_to_int)+1,
                                                      rnn_size, 
                                                      num_layers, 
                                                      vocab_to_int,
                                                      batch_size)
    
    # Create tensors for the training logits and inference logits
    training_logits = tf.identity(training_logits.rnn_output, 'logits')
    inference_logits = tf.identity(inference_logits.sample_id, name='predictions')
    
    # Create the weights for sequence_loss
    masks = tf.sequence_mask(summary_length, max_summary_length, dtype=tf.float32, name='masks')

    with tf.name_scope("optimization"):
        # Loss function
        cost = tf.contrib.seq2seq.sequence_loss(
            training_logits,
            targets,
            masks)

        # Optimizer
        optimizer = tf.train.AdamOptimizer(learning_rate)

        # Gradient Clipping
        gradients = optimizer.compute_gradients(cost)
        capped_gradients = [(tf.clip_by_value(grad, -5., 5.), var) for grad, var in gradients if grad is not None]
        train_op = optimizer.apply_gradients(capped_gradients)
print("Graph is built.")

我收到以下错误：

AttributeError: module 'tensorflow.compat.v1' has no attribute 'contrib'

我遇到了一些建议我安装 tensorflow 1.14 的答案，但是，这也给出了以下错误：

❯ pip install tensorflow==1.14
ERROR: Could not find a version that satisfies the requirement tensorflow==1.14 (from versions: 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.2.1, 2.2.2, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2, 2.3.0, 2.3.1, 2.3.2, 2.4.0rc0, 2.4.0rc1, 2.4.0rc2, 2.4.0rc3, 2.4.0rc4, 2.4.0, 2.4.1, 2.5.0rc0, 2.5.0rc1)
ERROR: No matching distribution found for tensorflow==1.14

请帮忙。

TIA。

[更新]

我尝试通过conda安装tensorflow 1.14，出现如下错误：

❯ conda install tensorflow==1.14
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
Examining @/win-64::__cuda==11.1=0:  67%|████████████████████████████████                | 2/3 [00:00<00:00, 13.28it/s]/                                                                                                                       -failed

UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:

Specifications:

  - tensorflow==1.14 -> python[version='3.6.*|3.7.*']
  - tensorflow==1.14 -> python[version='>=3.6,<3.7.0a0|>=3.7,<3.8.0a0']

Your python: python=3.8

If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.

The following specifications were found to be incompatible with your CUDA driver:

  - feature:/win-64::__cuda==11.1=0
  - feature:|@/win-64::__cuda==11.1=0

Your installed CUDA driver is: 11.1

Answer 1

如果您想使用 tf.contrib 库，请使用 Tensorflow ==1.14.0 或 1.15.0 它还需要 Python ==3.6/3.7。

Answer 2

Tf.contrib 在 Tensorflow >= 2.0 中被移除。 一些tf.contrib函数可以通过使用来使用

import tensorflow.compat.v1 as tf 
tf.disable_v2_behavior() 

为了使用 tf.contrib 库，请使用 Tensorflow ==1.14 或 1.15。

正如@hoefling 所说，Tensorflow 1.14 需要 Python ==3.6/3.7。