chainer.function_hooks.PrintHook¶
-
class
chainer.function_hooks.
PrintHook
(sep=None, end='n', file=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>, flush=True)[source]¶ Function hook that prints debug information.
This function hook outputs the debug information of input arguments of
forward
andbackward
methods involved in the hooked functions at preprocessing time (that is, just before each method is called).Unlike simple “debug print” technique, where users insert print functions at every function to be inspected, we can show the information of all functions involved with single
with
statement.Further, this hook enables us to show the information of
backward
methods without inserting print functions into Chainer’s library code.Parameters: - sep – (deprecated since v4.0.0) Ignored.
- end – Character to be added at the end of print function.
- file – Output file_like object that that redirect to.
- flush – If
True
, this hook forcibly flushes the text stream at the end of preprocessing.
Example
The basic usage is to use it with
with
statement.>>> from chainer import function_hooks >>> l = L.Linear(10, 10) >>> x = chainer.Variable(np.zeros((1, 10), np.float32)) >>> with chainer.function_hooks.PrintHook(): ... y = l(x) ... z = F.sum(y) ... z.backward()
In this example,
PrintHook
shows the debug information of forward propagation ofLinearFunction
(which is implicitly called byl
) andSum
(called byF.sum
) and backward propagation ofz
andy
.Methods
-
added
(function=None)[source]¶ Callback function invoked when a function hook is added
Parameters: function (FunctionNode) – Function object to which the function hook is added.
-
backward_postprocess
(function, in_data, out_grad)[source]¶ Callback function invoked after backward propagation.
Parameters: - function (FunctionNode) – Function object to which the function hook is registered.
- in_data (tuple of numpy.ndarray or tuple of cupy.ndarray) – Input of forward propagation.
- out_grad (tuple of numpy.ndarray or tuple of cupy.ndarray) – Gradient data of backward propagation.
-
backward_preprocess
(function, in_data, out_grad)[source]¶ Callback function invoked before backward propagation.
Parameters: - function (FunctionNode) – Function object to which the function hook is registered.
- in_data (tuple of numpy.ndarray or tuple of cupy.ndarray) – Input data of forward propagation.
- out_grad (tuple of numpy.ndarray or tuple of cupy.ndarray) – Gradient data of backward propagation.
-
deleted
(function=None)[source]¶ Callback function invoked when a function hook is deleted
Parameters: function (FunctionNode) – Function object to which the function hook is deleted.
-
forward_postprocess
(function, in_data)[source]¶ Callback function invoked after forward propagation.
Parameters: - function (FunctionNode) – Function object to which the function hook is registered.
- in_data (tuple of numpy.ndarray or tuple of cupy.ndarray) – Input data of forward propagation.
-
forward_preprocess
(function, in_data)[source]¶ Callback function invoked before forward propagation.
Parameters: - function (FunctionNode) – Function object to which the function hook is registered.
- in_data (tuple of numpy.ndarray or tuple of cupy.ndarray) – Input data of forward propagation.
Attributes
-
name
= 'PrintHook'¶