tf.convert_to_tensor

tf.convert_to_tensor(
    value,
    dtype=None,
    name=None,
    preferred_dtype=None
)

Defined in tensorflow/python/framework/ops.py.

See the guides: Building Graphs > Utility functions, Constants, Sequences, and Random Values, Control Flow, Higher Order Functions, Images, Inputs and Readers, Math, Neural Network, Sparse Tensors, Strings, Tensor Handle Operations, Tensor Transformations, Variables

Converts the given value to a Tensor.

This function converts Python objects of various types to Tensor objects. It accepts Tensor objects, numpy arrays, Python lists, and Python scalars. For example:

import numpy as np

def my_func(arg):
  arg = tf.convert_to_tensor(arg, dtype=tf.float32)
  return tf.matmul(arg, arg) + arg

# The following calls are equivalent.
value_1 = my_func(tf.constant([[1.0, 2.0], [3.0, 4.0]]))
value_2 = my_func([[1.0, 2.0], [3.0, 4.0]])
value_3 = my_func(np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32))

This function can be useful when composing a new operation in Python (such as my_func in the example above). All standard Python op constructors apply this function to each of their Tensor-valued inputs, which allows those ops to accept numpy arrays, Python lists, and scalars in addition to Tensor objects.

Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown.

Args:

• value: An object whose type has a registered Tensor conversion function.
• dtype: Optional element type for the returned tensor. If missing, the type is inferred from the type of value.
• name: Optional name to use if a new Tensor is created.
• preferred_dtype: Optional element type for the returned tensor, used when dtype is None. In some cases, a caller may not have a dtype in mind when converting to a tensor, so preferred_dtype can be used as a soft preference. If the conversion to preferred_dtype is not possible, this argument has no effect.

Returns:

An Output based on value.

Raises:

• TypeError: If no conversion function is registered for value.
• RuntimeError: If a registered conversion function returns an invalid value.