Python tensorflow.python.ops.gen_nn_ops._log_softmax() Examples

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Example #1
Source File: nn_ops.py    From lambda-packs with MIT License 6 votes vote down vote up 
def log_softmax(logits, dim=-1, name=None):
  """Computes log softmax activations.

  For each batch `i` and class `j` we have

      logsoftmax = logits - log(reduce_sum(exp(logits), dim))

  Args:
    logits: A non-empty `Tensor`. Must be one of the following types: `half`,
      `float32`, `float64`.
    dim: The dimension softmax would be performed on. The default is -1 which
      indicates the last dimension.
    name: A name for the operation (optional).

  Returns:
    A `Tensor`. Has the same type as `logits`. Same shape as `logits`.

  Raises:
    InvalidArgumentError: if `logits` is empty or `dim` is beyond the last
      dimension of `logits`.
  """
  return _softmax(logits, gen_nn_ops._log_softmax, dim, name)
Example #2
Source File: nn_ops.py    From auto-alt-text-lambda-api with MIT License 6 votes vote down vote up 
def log_softmax(logits, dim=-1, name=None):
  """Computes log softmax activations.

  For each batch `i` and class `j` we have

      logsoftmax = logits - log(reduce_sum(exp(logits), dim))

  Args:
    logits: A non-empty `Tensor`. Must be one of the following types: `half`,
      `float32`, `float64`.
    dim: The dimension softmax would be performed on. The default is -1 which
      indicates the last dimension.
    name: A name for the operation (optional).

  Returns:
    A `Tensor`. Has the same type as `logits`. Same shape as `logits`.

  Raises:
    InvalidArgumentError: if `logits` is empty or `dim` is beyond the last
      dimension of `logits`.
  """
  return _softmax(logits, gen_nn_ops._log_softmax, dim, name)
Example #3
Source File: nn_ops.py    From deep_image_model with Apache License 2.0 6 votes vote down vote up 
def log_softmax(logits, dim=-1, name=None):
  """Computes log softmax activations.

  For each batch `i` and class `j` we have

      logsoftmax = logits - log(reduce_sum(exp(logits), dim))

  Args:
    logits: A non-empty `Tensor`. Must be one of the following types: `half`,
      `float32`, `float64`.
    dim: The dimension softmax would be performed on. The default is -1 which
      indicates the last dimension.
    name: A name for the operation (optional).

  Returns:
    A `Tensor`. Has the same type as `logits`. Same shape as `logits`.

  Raises:
    InvalidArgumentError: if `logits` is empty or `dim` is beyond the last
      dimension of `logits`.
  """
  return _softmax(logits, gen_nn_ops._log_softmax, dim, name)
Example #4
Source File: nn_ops.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 6 votes vote down vote up 
def log_softmax(logits, dim=-1, name=None):
  """Computes log softmax activations.

  For each batch `i` and class `j` we have

      logsoftmax = logits - log(reduce_sum(exp(logits), dim))

  Args:
    logits: A non-empty `Tensor`. Must be one of the following types: `half`,
      `float32`, `float64`.
    dim: The dimension softmax would be performed on. The default is -1 which
      indicates the last dimension.
    name: A name for the operation (optional).

  Returns:
    A `Tensor`. Has the same type as `logits`. Same shape as `logits`.

  Raises:
    InvalidArgumentError: if `logits` is empty or `dim` is beyond the last
      dimension of `logits`.
  """
  return _softmax(logits, gen_nn_ops._log_softmax, dim, name)
Example #5
Source File: nn_ops.py    From keras-lambda with MIT License 6 votes vote down vote up 
def log_softmax(logits, dim=-1, name=None):
  """Computes log softmax activations.

  For each batch `i` and class `j` we have

      logsoftmax = logits - log(reduce_sum(exp(logits), dim))

  Args:
    logits: A non-empty `Tensor`. Must be one of the following types: `half`,
      `float32`, `float64`.
    dim: The dimension softmax would be performed on. The default is -1 which
      indicates the last dimension.
    name: A name for the operation (optional).

  Returns:
    A `Tensor`. Has the same type as `logits`. Same shape as `logits`.

  Raises:
    InvalidArgumentError: if `logits` is empty or `dim` is beyond the last
      dimension of `logits`.
  """
  return _softmax(logits, gen_nn_ops._log_softmax, dim, name)