提交 869ef01d 编写于 作者: F fengjiayi

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into kernel_of_increment_op

# Channel Design
## Introduction
A Channel is a data structure that allows for synchronous interprocess
communication via message passing. It is a fundemental component of CSP
(communicating sequential processes), and allows for users to pass data
between threads without having to worry about synchronization.
## How to use it
Paddle offers python APIs to open and close channels, along with sending
and receiving data to/from a channel.
### Create a channel
Creates a new channel that takes in variables of a specific dtype.
- **fluid.make_channel(dtype, capacity=0)**
- **dtype**: The data type of variables being sent/received through channel
- **capacity**: The capacity of the channel. A capacity of 0 represents
an unbuffered channel. Capacity > 0 represents a buffered channel
```
ch = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR, 10)
```
### Close a channel
Closes a channel. Any pending senders and receivers will be awoken during
this time. Receivers can still receive from a closed channel, but senders
are not allowed to send any additional data to the channel (Paddle will
raise an exception if users try to send to a closed channel.)
- **fluid.channel_close(channel)**
```
fluid.channel_close(ch)
```
### Send data to a channel
Sends a variable to a channel. Currently, variables of dtype `LoDTensor`,
`LoDRankTable`, `LoDTensorArray`, `SelectedRows`, `ReaderHolder`, and
`ChannelHolder` are supported.
By default, the data of the Variable is moved from the sender to the receiver,
however the user can optionally copy the data before performing the send.
- **channel_send(channel, variable, is_copy=False)**
- **channel**: The channel to send the variable to
- **variable**: The variable to send to the channel
- **is_copy**: If set to True, channel_send will perform a variable assign
to copy the source variable to a new variable to be sent.
```
ch = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR)
var = fill_constant(shape=[1],dtype=core.VarDesc.VarType.INT32, value=100)
fluid.channel_send(ch, var, True)
```
### Receive data from a channel
Receives a variable from a channel. The data of the variable is moved to the
receiving variable.
- **channel_recv(channel, return_variable)**
- **channel**: The channel to receive the variable from
- **return_variable**: The destination variable used to store the data of the
variable received from the channel
```
ch = fluid.make_channel(dtype=core.VarDesc.VarType.LOD_TENSOR)
var = fill_constant(shape=[1],dtype=core.VarDesc.VarType.INT32, value=-1)
fluid.channel_recv(ch, var)
```
## How it Works
Channels provides a simple interface for different threads to share data.
To support the synchronization requirements, channels utilizes a series of
internal queues, locks, and conditional variables.
### QueueMessage
QueueMessage encapsulates the state of the channel send/receive operation to be
put in the **sendq/recvq**. It contains a condition variable used to lock the
thread (when there are no available sends/receives). In addition, it contains
a callback function to notify a thread when the QueueMessage is being
processed by the channel.
### Queues
- **buff_**: This queue holds the data buffer in a buffered channel. The
capacity is set to the capacity of the channel. This data buffer is not
used in an unbuffered channel.
- **sendq**: This queue holds the QueueMessage of any pending senders of a
channel. When a thread performs a channel_send operation on the channel, the
channel_send operation will put a new QueueMessage on the sendq and block the
current thread under two conditions:
1. The channel is buffered and is full
2. The channel is unbuffered and does not have a receiver
- **recvq**: This queue holds the QueueMessage of any pending receivers of a
channel. When a thread performs a channel_recv operation on the channel, the
channel_recv operation will put a new QueueMessage on the recvq and block the
current thread under two conditions:
1. The channel is buffered and there is no data on the buff_
2. The channel is unbuffered and does not have a sender
### State diagram
#### Channel Send
<p align="center">
<img src="./images/channel_send.png"/><br/>
</p>
#### Channel Receive
<p align="center">
<img src="./images/channel_recv.png"/><br/>
</p>
## Limitations and Considerations
### Variable Copy
In golang, variables in channels are copied from the sender to the receiver.
In Paddle, the data from our variables are **moved** from sender to receiver.
As a result, these variables should not be used after they are sent. We
provide a flag in channel_send method to allow users to copy the variable to
be sent before it is sent.
Please note that this is acheived by adding an **assign** operator and creating
a temporary variable that is sent in place of the original variable. Please
note that **assign** operator has limited support for only certain variables
datatypes.
......@@ -100,7 +100,7 @@ cc_test(init_test SRCS init_test.cc DEPS init)
cc_test(op_kernel_type_test SRCS op_kernel_type_test.cc DEPS place device_context framework_proto)
cc_test(cow_ptr_tests SRCS details/cow_ptr_test.cc)
cc_test(channel_test SRCS channel_test.cc)
# cc_test(channel_test SRCS channel_test.cc)
cc_test(tuple_test SRCS tuple_test.cc )
cc_test(concurrency_test SRCS concurrency_test.cc DEPS go_op channel_close_op channel_create_op
channel_send_op channel_recv_op sum_op select_op elementwise_add_op compare_op
......
......@@ -398,7 +398,6 @@ class LayerHelper(object):
return input_var
if isinstance(act, basestring):
act = {'type': act}
tmp = self.create_tmp_variable(dtype=input_var.dtype)
if 'use_mkldnn' in self.kwargs:
act['use_mkldnn'] = self.kwargs.get('use_mkldnn')
......@@ -408,9 +407,9 @@ class LayerHelper(object):
self.append_op(
type=act_type,
inputs={"X": [input_var]},
outputs={"Out": [tmp]},
outputs={"Out": [input_var]},
attrs=act)
return tmp
return input_var
def _get_default_initializer(self, dtype):
if dtype is None or dtype_is_floating(dtype) is True:
......
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