From d1fe87582f73ac99056b3accef20bcc0ae0665a0 Mon Sep 17 00:00:00 2001 From: qiaolongfei Date: Mon, 4 Sep 2017 22:10:10 -0700 Subject: [PATCH] use block in demo code --- doc/design/var_desc.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/doc/design/var_desc.md b/doc/design/var_desc.md index 545ff161ef0..9175d151931 100644 --- a/doc/design/var_desc.md +++ b/doc/design/var_desc.md @@ -61,24 +61,26 @@ fc2 = layer.fc(input=fc1, output_size=20) 1. `operator`. Variable should record which operator produce itself. The reaon is: - we use pd.eval(targets=[var1, var2]) to run the related ops to get the value of var1 and var2. var.op is used to trace the dependency of the current variable. +In PaddlePaddle, we use Block to describe Computation Graph, so in the code we will use Block but not Graph. + ```python import VarDesc import LoDTensorDesc import framework def AddInitialOperator(variable, initializer): - # add an initialize Operator to graph to init this Variable + # add an initialize Operator to block to init this Variable class Variable(object): def __init__(self, name, dims, type, initializer): - self._graph = get_default_graph() + self._block = get_default_block() self._name = name self.op = None tensor_desc = LoDTensorDesc(data_type=type, dims=dims) _var_desc = VarDesc(name=name, lod_tensor=tensor_desc) self._var = framework.CreateVar(_var_desc) - self._graph.add_var(self) + self._block.add_var(self) # add initial op according to initializer if initializer is not None: @@ -117,6 +119,6 @@ x = Variable(dims=[-1, 640, 480]) y = layer.fc(x, output_size=100) z = layer.fc(y, output_size=200) -paddle.train(z, ...) -print(y) +paddle.eval(targets=[z], ...) +print(z) ``` -- GitLab