To print the shape of a tensor in TensorFlow, you can use the TensorFlow session to run the tensor and then use the `shape`

attribute to access the shape of the tensor. Here is an example code snippet that demonstrates how to print the shape of a tensor in TensorFlow:

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import tensorflow as tf # Create a sample tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # Start a TensorFlow session with tf.Session() as sess: # Run the tensor and get the shape shape = sess.run(tf.shape(tensor)) # Print the shape of the tensor print(shape) |

In this code snippet, we first create a sample tensor using the `tf.constant`

function. Then we start a TensorFlow session using the `tf.Session()`

context manager. Inside the session, we run the tensor using `sess.run(tf.shape(tensor))`

to get the shape of the tensor. Finally, we print the shape of the tensor using the `print`

function.

## How to view tensor shape in tensorflow?

In TensorFlow, you can view the shape of a tensor using the `.shape`

attribute. Here is an example of how to view the shape of a tensor in TensorFlow:

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # View the shape of the tensor print(tensor.shape) |

This will output the shape of the tensor, which in this case is `(2, 3)`

indicating that the tensor has 2 rows and 3 columns.

## What is the technique to retrieve tensor shape in tensorflow?

In TensorFlow, you can retrieve the shape of a tensor using the `tf.shape()`

function.

Here is an example code snippet that demonstrates how to retrieve the shape of a tensor in TensorFlow:

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # Get the shape of the tensor tensor_shape = tf.shape(tensor) # Print the shape of the tensor print(tensor_shape) |

This will output the shape of the tensor as a TensorFlow tensor object. If you want to retrieve the shape as a numpy array, you can do so by evaluating the tensor shape using a TensorFlow session:

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # Get the shape of the tensor tensor_shape = tf.shape(tensor) # Start a TensorFlow session with tf.Session() as sess: # Evaluate the tensor shape shape = sess.run(tensor_shape) # Print the shape as a numpy array print(shape) |

This will output the shape of the tensor as a numpy array.

## What is the function to print tensor shape in tensorflow?

In TensorFlow, you can print the shape of a tensor using the shape attribute. Here's an example:

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # Print the shape of the tensor print(tensor.shape) |

This will output the shape of the tensor, which in this case is (2, 3) indicating that it is a 2-dimensional tensor with 2 rows and 3 columns.

## How to retrieve tensor shape in tensorflow?

In TensorFlow, you can retrieve the shape of a tensor using the `tf.shape()`

function. Here is an example code snippet demonstrating how to do this:

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # Retrieve the shape of the tensor tensor_shape = tf.shape(tensor) # Create a TensorFlow session with tf.Session() as sess: # Run the session to get the shape shape = sess.run(tensor_shape) print(shape) |

In this code snippet, we first create a tensor using `tf.constant()`

, then use `tf.shape()`

to retrieve the shape of the tensor. Finally, we run a TensorFlow session to compute and print out the shape of the tensor.

## What is the technique to get tensor size in tensorflow?

To get the size of a tensor in TensorFlow, you can use the shape attribute of the tensor object. Here is an example:

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import tensorflow as tf # Create a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # Get the shape of the tensor tensor_size = tf.size(tensor) # Create a TensorFlow session with tf.Session() as sess: print(sess.run(tensor_size)) |

This will output the total number of elements in the tensor, which in this case is 6.

## How to determine tensor shape in tensorflow?

In TensorFlow, you can determine the shape of a tensor by using the `tf.shape()`

function. This function returns the shape of the input tensor as a 1-D integer tensor.

Here is an example code snippet that demonstrates how to determine the shape of a tensor in TensorFlow:

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import tensorflow as tf # Define a tensor tensor = tf.constant([[1, 2, 3], [4, 5, 6]]) # Get the shape of the tensor shape = tf.shape(tensor) # Create a TensorFlow session with tf.Session() as sess: print("Shape of the tensor: ", sess.run(shape)) |

When you run this code snippet, it will print out the shape of the tensor `[2 3]`

, indicating that the tensor has 2 rows and 3 columns.