Keras backend API.
Classes
class name_scope
: A context manager for use when defining a Python op.
Functions
abs(...)
: Element-wise absolute value.
all(...)
: Bitwise reduction (logical AND).
any(...)
: Bitwise reduction (logical OR).
arange(...)
: Creates a 1D tensor containing a sequence of integers.
argmax(...)
: Returns the index of the maximum value along an axis.
argmin(...)
: Returns the index of the minimum value along an axis.
backend(...)
: Publicly accessible method for determining the current backend.
batch_dot(...)
: Batchwise dot product.
batch_flatten(...)
: Turn a nD tensor into a 2D tensor with same 0th dimension.
batch_get_value(...)
: Returns the value of more than one tensor variable.
batch_normalization(...)
: Applies batch normalization on x given mean, var, beta and gamma.
batch_set_value(...)
: Sets the values of many tensor variables at once.
bias_add(...)
: Adds a bias vector to a tensor.
binary_crossentropy(...)
: Binary crossentropy between an output tensor and a target tensor.
cast(...)
: Casts a tensor to a different dtype and returns it.
cast_to_floatx(...)
: Cast a Numpy array to the default Keras float type.
categorical_crossentropy(...)
: Categorical crossentropy between an output tensor and a target tensor.
clear_session(...)
: Destroys the current TF graph and creates a new one.
clip(...)
: Element-wise value clipping.
concatenate(...)
: Concatenates a list of tensors alongside the specified axis.
constant(...)
: Creates a constant tensor.
conv1d(...)
: 1D convolution.
conv2d(...)
: 2D convolution.
conv2d_transpose(...)
: 2D deconvolution (i.e.
conv3d(...)
: 3D convolution.
cos(...)
: Computes cos of x element-wise.
count_params(...)
: Returns the static number of elements in a variable or tensor.
ctc_batch_cost(...)
: Runs CTC loss algorithm on each batch element.
ctc_decode(...)
: Decodes the output of a softmax.
ctc_label_dense_to_sparse(...)
: Converts CTC labels from dense to sparse.
cumprod(...)
: Cumulative product of the values in a tensor, alongside the specified axis.
cumsum(...)
: Cumulative sum of the values in a tensor, alongside the specified axis.
depthwise_conv2d(...)
: 2D convolution with separable filters.
dot(...)
: Multiplies 2 tensors (and/or variables) and returns a tensor.
dropout(...)
: Sets entries in x
to zero at random, while scaling the entire tensor.
dtype(...)
: Returns the dtype of a Keras tensor or variable, as a string.
elu(...)
: Exponential linear unit.
epsilon(...)
: Returns the value of the fuzz factor used in numeric expressions.
equal(...)
: Element-wise equality between two tensors.
eval(...)
: Evaluates the value of a variable.
exp(...)
: Element-wise exponential.
expand_dims(...)
: Adds a 1-sized dimension at index "axis".
eye(...)
: Instantiate an identity matrix and returns it.
flatten(...)
: Flatten a tensor.
floatx(...)
: Returns the default float type, as a string.
foldl(...)
: Reduce elems using fn to combine them from left to right.
foldr(...)
: Reduce elems using fn to combine them from right to left.
function(...)
: Instantiates a Keras function.
gather(...)
: Retrieves the elements of indices indices
in the tensor reference
.
get_session(...)
: Returns the TF session to be used by the backend.
get_uid(...)
: Associates a string prefix with an integer counter in a TensorFlow graph.
get_value(...)
: Returns the value of a variable.
gradients(...)
: Returns the gradients of loss
w.r.t. variables
.
greater(...)
: Element-wise truth value of (x > y).
greater_equal(...)
: Element-wise truth value of (x >= y).
hard_sigmoid(...)
: Segment-wise linear approximation of sigmoid.
image_data_format(...)
: Returns the default image data format convention.
in_test_phase(...)
: Selects x
in test phase, and alt
otherwise.
in_top_k(...)
: Returns whether the targets
are in the top k
predictions
.
in_train_phase(...)
: Selects x
in train phase, and alt
otherwise.
int_shape(...)
: Returns the shape of tensor or variable as a tuple of int or None entries.
is_keras_tensor(...)
: Returns whether x
is a Keras tensor.
is_sparse(...)
: Returns whether a tensor is a sparse tensor.
l2_normalize(...)
: Normalizes a tensor wrt the L2 norm alongside the specified axis.
learning_phase(...)
: Returns the learning phase flag.
learning_phase_scope(...)
: Provides a scope within which the learning phase is equal to value
.
less(...)
: Element-wise truth value of (x < y).
less_equal(...)
: Element-wise truth value of (x <= y).
local_conv1d(...)
: Apply 1D conv with un-shared weights.
local_conv2d(...)
: Apply 2D conv with un-shared weights.
log(...)
: Element-wise log.
manual_variable_initialization(...)
: Sets the manual variable initialization flag.
map_fn(...)
: Map the function fn over the elements elems and return the outputs.
max(...)
: Maximum value in a tensor.
maximum(...)
: Element-wise maximum of two tensors.
mean(...)
: Mean of a tensor, alongside the specified axis.
min(...)
: Minimum value in a tensor.
minimum(...)
: Element-wise minimum of two tensors.
moving_average_update(...)
: Compute the moving average of a variable.
ndim(...)
: Returns the number of axes in a tensor, as an integer.
normalize_batch_in_training(...)
: Computes mean and std for batch then apply batch_normalization on batch.
not_equal(...)
: Element-wise inequality between two tensors.
one_hot(...)
: Computes the one-hot representation of an integer tensor.
ones(...)
: Instantiates an all-ones variable and returns it.
ones_like(...)
: Instantiates an all-ones variable of the same shape as another tensor.
permute_dimensions(...)
: Permutes axes in a tensor.
placeholder(...)
: Instantiates a placeholder tensor and returns it.
pool2d(...)
: 2D Pooling.
pool3d(...)
: 3D Pooling.
pow(...)
: Element-wise exponentiation.
print_tensor(...)
: Prints message
and the tensor value when evaluated.
prod(...)
: Multiplies the values in a tensor, alongside the specified axis.
random_binomial(...)
: Returns a tensor with random binomial distribution of values.
random_normal(...)
: Returns a tensor with normal distribution of values.
random_normal_variable(...)
: Instantiates a variable with values drawn from a normal distribution.
random_uniform(...)
: Returns a tensor with uniform distribution of values.
random_uniform_variable(...)
: Instantiates a variable with values drawn from a uniform distribution.
relu(...)
: Rectified linear unit.
repeat(...)
: Repeats a 2D tensor.
repeat_elements(...)
: Repeats the elements of a tensor along an axis, like np.repeat
.
reset_uids(...)
: Resets graph identifiers.
reshape(...)
: Reshapes a tensor to the specified shape.
resize_images(...)
: Resizes the images contained in a 4D tensor.
resize_volumes(...)
: Resizes the volume contained in a 5D tensor.
reverse(...)
: Reverse a tensor along the specified axes.
rnn(...)
: Iterates over the time dimension of a tensor.
round(...)
: Element-wise rounding to the closest integer.
separable_conv2d(...)
: 2D convolution with separable filters.
set_epsilon(...)
: Sets the value of the fuzz factor used in numeric expressions.
set_floatx(...)
: Sets the default float type.
set_image_data_format(...)
: Sets the value of the image data format convention.
set_learning_phase(...)
: Sets the learning phase to a fixed value.
set_session(...)
: Sets the global TensorFlow session.
set_value(...)
: Sets the value of a variable, from a Numpy array.
shape(...)
: Returns the symbolic shape of a tensor or variable.
sigmoid(...)
: Element-wise sigmoid.
sign(...)
: Element-wise sign.
sin(...)
: Computes sin of x element-wise.
softmax(...)
: Softmax of a tensor.
softplus(...)
: Softplus of a tensor.
softsign(...)
: Softsign of a tensor.
sparse_categorical_crossentropy(...)
: Categorical crossentropy with integer targets.
spatial_2d_padding(...)
: Pads the 2nd and 3rd dimensions of a 4D tensor.
spatial_3d_padding(...)
: Pads 5D tensor with zeros along the depth, height, width dimensions.
sqrt(...)
: Element-wise square root.
square(...)
: Element-wise square.
squeeze(...)
: Removes a 1-dimension from the tensor at index "axis".
stack(...)
: Stacks a list of rank R
tensors into a rank R+1
tensor.
std(...)
: Standard deviation of a tensor, alongside the specified axis.
stop_gradient(...)
: Returns variables
but with zero gradient w.r.t. every other variable.
sum(...)
: Sum of the values in a tensor, alongside the specified axis.
switch(...)
: Switches between two operations depending on a scalar value.
tanh(...)
: Element-wise tanh.
temporal_padding(...)
: Pads the middle dimension of a 3D tensor.
tile(...)
: Creates a tensor by tiling x
by n
.
to_dense(...)
: Converts a sparse tensor into a dense tensor and returns it.
transpose(...)
: Transposes a tensor and returns it.
truncated_normal(...)
: Returns a tensor with truncated random normal distribution of values.
update_add(...)
: Update the value of x
by adding increment
.
update_sub(...)
: Update the value of x
by subtracting decrement
.
var(...)
: Variance of a tensor, alongside the specified axis.
variable(...)
: Instantiates a variable and returns it.
zeros(...)
: Instantiates an all-zeros variable and returns it.
zeros_like(...)
: Instantiates an all-zeros variable of the same shape as another tensor.