TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
TensorProto is mostly used to generate numpy array.
Function Used:
- make_tensor_proto: This function accepts values that need to be put in TensorProto with other optional arguments.
Example 1:
Python3
# importing the library import tensorflow as tf # Initializing Input value = tf.constant([1, 15], dtype = tf.float64) # Printing the Input print("Value: ", value) # Getting TensorProto res = tf.make_tensor_proto(value) # Printing the resulting tensor print("Result: ", res) |
Output:
Value: tf.Tensor([ 1. 15.], shape=(2, ), dtype=float64)
Result: dtype: DT_DOUBLE
tensor_shape {
dim {
size: 2
}
}
tensor_content: "\000\000\000\000\000\000\360?\000\000\000\000\000\000.@"
Example 2: This example uses python array to generate TensorProto.
Python3
# importing the library import tensorflow as tf # Initializing Input value = [1, 2, 3, 4] # Printing the Input print("Value: ", value) # Getting TensorProto res = tf.make_tensor_proto(value) # Printing the resulting tensor print("Result: ", res) |
Output:
Value: [1, 2, 3, 4]
Result: dtype: DT_INT32
tensor_shape {
dim {
size: 4
}
}
tensor_content: "\001\000\000\000\002\000\000\000\003\000\000\000\004\000\000\000"
