Tensorflow中所有dtype = float32的打印值（權重）

Question

是否有簡便的方法可以打印dtype=float32的值而不需要placeholders和feed_dict？這個過程很尷尬，需要爲每個操作單獨定義。說我有inceptionv3模型與數百名操作：

op = sess.graph.get_operations() 
    for m in op : 
    print(m.values()) 

這些和他們中的一些混合：

... 
(<tf.Tensor 'pool_3:0' shape=(?, ?, ?, 2048) dtype=float32>,) 
(<tf.Tensor 'pool_3/_reshape/shape:0' shape=(2,) dtype=int32>,) 
(<tf.Tensor 'pool_3/_reshape:0' shape=(1, 2048) dtype=float32>,) 
(<tf.Tensor 'softmax/weights_quint8_const:0' shape=(2048, 1008) dtype=quint8>,) 
(<tf.Tensor 'softmax/weights_min:0' shape=() dtype=float32>,) 
(<tf.Tensor 'softmax/weights_max:0' shape=() dtype=float32>,) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_reshape_dims:0' shape=(1,) dtype=int32>,) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_reduction_dims:0' shape=(1,) dtype=int32>,) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_reshape_pool_3/_reshape:0' shape=(2048,) dtype=float32>,) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_min_pool_3/_reshape:0' shape=() dtype=float32>,) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_max_pool_3/_reshape:0' shape=() dtype=float32>,) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_quantize_pool_3/_reshape:0' shape=(1, 2048) dtype=quint8>, <tf.Tensor 'softmax/logits/MatMul_eightbit_quantize_pool_3/_reshape:1' shape=() dtype=float32>, <tf.Tensor 'softmax/logits/MatMul_eightbit_quantize_pool_3/_reshape:2' shape=() dtype=float32>) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_quantized_bias_add:0' shape=(1, 1008) dtype=qint32>, <tf.Tensor 'softmax/logits/MatMul_eightbit_quantized_bias_add:1' shape=() dtype=float32>, <tf.Tensor 'softmax/logits/MatMul_eightbit_quantized_bias_add:2' shape=() dtype=float32>) 
(<tf.Tensor 'softmax/logits/MatMul_eightbit_quantize_down:0' shape=(1, 1008) dtype=quint8>, <tf.Tensor 'softmax/logits/MatMul_eightbit_quantize_down:1' shape=() dtype=float32>, <tf.Tensor 'softmax/logits/MatMul_eightbit_quantize_down:2' shape=() dtype=float32>) 
(<tf.Tensor 'softmax/biases_quint8_const:0' shape=(1008,) dtype=quint8>,) 
(<tf.Tensor 'softmax/biases_min:0' shape=() dtype=float32>,) 
(<tf.Tensor 'softmax/biases_max:0' shape=() dtype=float32>,) 
(<tf.Tensor 'softmax/logits_eightbit_quantized_bias_add:0' shape=(1, 1008) dtype=qint32>, <tf.Tensor 'softmax/logits_eightbit_quantized_bias_add:1' shape=() dtype=float32>, <tf.Tensor 'softmax/logits_eightbit_quantized_bias_add:2' shape=() dtype=float32>) 
(<tf.Tensor 'softmax/logits_eightbit_quantize_down:0' shape=(1, 1008) dtype=quint8>, <tf.Tensor 'softmax/logits_eightbit_quantize_down:1' shape=() dtype=float32>, <tf.Tensor 'softmax/logits_eightbit_quantize_down:2' shape=() dtype=float32>) 
(<tf.Tensor 'softmax/logits:0' shape=(1, 1008) dtype=float32>,) 
(<tf.Tensor [] shape=(1, 1008) dtype=float32>,) 

有沒有一種簡單的方法，在一次打印所有這些浮點類型的值？

Answer 1

您可以使用類似

from pprint import pprint 
pprint([out 
    for op in tf.get_default_graph().get_operations() if op.type != 'Placeholder' 
    for out in op.values() if out.dtype == tf.float32]) 

飼料類型的字典是標準的Python字典，使他們不應該出現的圖形操作。

編輯

要得到他們的價值觀，你需要運行它們：

out_val = sess.run([out 
    for op in tf.get_default_graph().get_operations() if op.type != 'Placeholder' 
    for out in op.values() if out.dtype == tf.float32], 
    feed_dict=my_feed_dict)