kerasでbackend その4

#概要
kerasでbackendにsubtractが、無い。


#一覧

```
K.abs						Element-wise absolute value.
K.all						Bitwise reduction (logical AND).
K.any						Bitwise reduction (logical OR).
K.arange					Creates a 1D tensor containing a sequence of integers.
K.argmax					Returns the index of the maximum value along an axis.
K.argmin					Returns the index of the minimum value along an axis.
K.backend					Active Keras backend
K.batch_dot					Batchwise dot product.
K.batch_flatten				Turn a nD tensor into a 2D tensor with same 1st dimension.
K.batch_get_value			Returns the value of more than one tensor variable.
K.batch_normalization		Applies batch normalization on x given mean, var, beta and gamma.
K.batch_set_value			Sets the values of many tensor variables at once.
K.bias_add					Adds a bias vector to a tensor.
K.binary_crossentropy		Binary crossentropy between an output tensor and a target tensor.
K.cast_to_floatx			Cast an array to the default Keras float type.
K.cast						Casts a tensor to a different dtype and returns it.
K.categorical_crossentropy	Categorical crossentropy between an output tensor and a target tensor.
K.clear_session				Destroys the current TF graph and creates a new one.
K.clip						Element-wise value clipping.
K.concatenate				Concatenates a list of tensors alongside the specified axis.
K.constant					Creates a constant tensor.
K.conv1d					1D convolution.
K.conv2d_transpose			2D deconvolution (i.e. transposed convolution).
K.conv2d					2D convolution.
K.conv3d_transpose			3D deconvolution (i.e. transposed convolution).
K.conv3d					3D convolution.
K.cos						Computes cos of x element-wise.
K.count_params				Returns the static number of elements in a Keras variable or tensor.
K.ctc_batch_cost			Runs CTC loss algorithm on each batch element.
K.ctc_decode				Decodes the output of a softmax.
K.ctc_label_dense_to_sparse	Converts CTC labels from dense to sparse.
K.cumprod					Cumulative product of the values in a tensor, alongside the specified axis.
K.cumsum					Cumulative sum of the values in a tensor, alongside the specified axis.
K.depthwise_conv2d			2D convolution with separable filters.
K.dot						Multiplies 2 tensors (and/or variables) and returns a tensor.
K.dropout					Sets entries in x to zero at random, while scaling the entire tensor.
K.dtype						Returns the dtype of a Keras tensor or variable, as a string.
K.elu						Exponential linear unit.
K.epsilon 					Fuzz factor used in numeric expressions.
K.equal						Element-wise equality between two tensors.
K.eval						Evaluates the value of a variable.
K.exp						Element-wise exponential.
K.expand_dims				Adds a 1-sized dimension at index "axis".
K.eye						Instantiate an identity matrix and returns it.
K.flatten					Flatten a tensor.
K.floatx 					Default float type
K.foldl						Reduce elems using fn to combine them from left to right.
K.foldr						Reduce elems using fn to combine them from right to left.
K.function					Instantiates a Keras function
K.gather					Retrieves the elements of indices indices in the tensor reference.
K.get_session				TF session to be used by the backend.
K.get_uid					Get the uid for the default graph.
K.get_value					Returns the value of a variable.
K.get_variable_shape		Returns the shape of a variable.
K.gradients					Returns the gradients of variables w.r.t. loss.
K.greater_equal				Element-wise truth value of (x >= y).
K.greater					Element-wise truth value of (x > y).
K.hard_sigmoid				Segment-wise linear approximation of sigmoid.
K.identity					Returns a tensor with the same content as the input tensor.
K.image_data_format 		Default image data format convention ('channels_first' or 'channels_last').
K.in_test_phase				Selects x in test phase, and alt otherwise.
K.in_top_k					Returns whether the targets are in the top k predictions.
K.in_train_phase			Selects x in train phase, and alt otherwise.
K.int_shape					Returns the shape of tensor or variable as a list of int or NULL entries.
K.is_keras_tensor			Returns whether x is a Keras tensor.
K.is_placeholder			Returns whether x is a placeholder.
K.is_sparse					Returns whether a tensor is a sparse tensor.
K.l2_normalize				Normalizes a tensor wrt the L2 norm alongside the specified axis.
K.learning_phase			Returns the learning phase flag.
K.less_equal				Element-wise truth value of (x <= y).
K.less						Element-wise truth value of (x < y).
K.local_conv1d				Apply 1D conv with un-shared weights.
K.local_conv2d				Apply 2D conv with un-shared weights.
K.log						Element-wise log.
K.logsumexp					Computes log(sum(exp(elements across dimensions of a tensor))).
K.manual_variable_initialization	Sets the manual variable initialization flag.
K.map_fn					Map the function fn over the elements elems and return the outputs.
K.max						Maximum value in a tensor.
K.maximum					Element-wise maximum of two tensors.
K.mean						Mean of a tensor, alongside the specified axis.
K.min						Minimum value in a tensor.
K.minimum					Element-wise minimum of two tensors.
K.moving_average_update		Compute the moving average of a variable.
K.ndim						Returns the number of axes in a tensor, as an integer.
K.normalize_batch_in_training	Computes mean and std for batch then apply batch_normalization on batch.
K.not_equal					Element-wise inequality between two tensors.
K.one_hot					Computes the one-hot representation of an integer tensor.
K.ones_like					Instantiates an all-ones variable of the same shape as another tensor.
K.ones						Instantiates an all-ones tensor variable and returns it.
K.permute_dimensions		Permutes axes in a tensor.
K.placeholder				Instantiates a placeholder tensor and returns it.
K.pool2d					2D Pooling.
K.pool3d					3D Pooling.
K.pow						Element-wise exponentiation.
K.print_tensor				Prints message and the tensor value when evaluated.
K.prod						Multiplies the values in a tensor, alongside the specified axis.
K.random_binomial			Returns a tensor with random binomial distribution of values.
K.random_normal_variable	Instantiates a variable with values drawn from a normal distribution.
K.random_normal				Returns a tensor with normal distribution of values.
K.random_uniform_variable	Instantiates a variable with values drawn from a uniform distribution.
K.random_uniform			Returns a tensor with uniform distribution of values.
K.relu						Rectified linear unit.
K.repeat_elements			Repeats the elements of a tensor along an axis.
K.repeat					Repeats a 2D tensor.
K.reset_uids				Reset graph identifiers.
K.reshape					Reshapes a tensor to the specified shape.
K.resize_images				Resizes the images contained in a 4D tensor.
K.resize_volumes			Resizes the volume contained in a 5D tensor.
K.reverse					Reverse a tensor along the specified axes.
K.rnn						Iterates over the time dimension of a tensor
K.round						Element-wise rounding to the closest integer.
K.separable_conv2d			2D convolution with separable filters.
K.set_epsilon				Fuzz factor used in numeric expressions.
K.set_floatx				Default float type
K.set_learning_phase		Sets the learning phase to a fixed value.
K.set_value					Sets the value of a variable, from an R array.
K.set_session				TF session to be used by the backend.
K.set_image_data_format		Default image data format convention ('channels_first' or 'channels_last').
K.shape						Returns the symbolic shape of a tensor or variable.
K.sigmoid					Element-wise sigmoid.
K.sign						Element-wise sign.
K.sin						Computes sin of x element-wise.
K.softmax					Softmax of a tensor.
K.softplus					Softplus of a tensor.
K.softsign					Softsign of a tensor.
K.sparse_categorical_crossentropy	Categorical crossentropy with integer targets.
K.spatial_2d_padding		Pads the 2nd and 3rd dimensions of a 4D tensor.
K.spatial_3d_padding		Pads 5D tensor with zeros along the depth, height, width dimensions.
K.sqrt						Element-wise square root.
K.square					Element-wise square.
K.squeeze					Removes a 1-dimension from the tensor at index "axis".
K.stack						Stacks a list of rank R tensors into a rank R+1 tensor.
K.std						Standard deviation of a tensor, alongside the specified axis.
K.stop_gradient				Returns variables but with zero gradient w.r.t. every other variable.
K.sum						Sum of the values in a tensor, alongside the specified axis.
K.switch					Switches between two operations depending on a scalar value.
K.tanh						Element-wise tanh.
K.temporal_padding			Pads the middle dimension of a 3D tensor.
K.tile						Creates a tensor by tiling x by n.
K.to_dense					Converts a sparse tensor into a dense tensor and returns it.
K.transpose					Transposes a tensor and returns it.
K.truncated_normal			Returns a tensor with truncated random normal distribution of values.
K.update_add				Update the value of x by adding increment.
K.update_sub				Update the value of x by subtracting decrement.
K.update					Update the value of x to new_x.
K.var						Variance of a tensor, alongside the specified axis.
K.variable					Instantiates a variable and returns it.
K.zeros_like				Instantiates an all-zeros variable of the same shape as another tensor.
K.zeros						Instantiates an all-zeros variable and returns it.



```

以上。