From e9a92e3ed84856f5749eb026bd7f7d29dcbc3c34 Mon Sep 17 00:00:00 2001 From: superjom Date: Tue, 8 Aug 2017 19:12:14 +0800 Subject: [PATCH] add fc test --- .../paddle/v2/framework/tests/test_fc_op.py | 39 +++++++++--------- .../v2/framework/tests/test_recurrent_op.py | 40 +++++++++++++------ 2 files changed, 47 insertions(+), 32 deletions(-) diff --git a/python/paddle/v2/framework/tests/test_fc_op.py b/python/paddle/v2/framework/tests/test_fc_op.py index e24435839d3..4d5af08e156 100644 --- a/python/paddle/v2/framework/tests/test_fc_op.py +++ b/python/paddle/v2/framework/tests/test_fc_op.py @@ -1,28 +1,24 @@ -import paddle.v2.framework.core as core import unittest -import numpy +import numpy as np +import paddle.v2.framework.core as core from paddle.v2.framework.op import Operator class TestFc(unittest.TestCase): + def setUp(self): + self.x_np_data = np.random.random((1000, 784)) + self.W_np_data = np.random.random((784, 100)) + def test_fc(self): scope = core.Scope() place = core.CPUPlace() - x = scope.new_var("X") - - x_tensor = x.get_tensor() - x_tensor.set_dims([1000, 784]) - x_tensor.alloc_float(place) + x_tensor = scope.new_var("X").get_tensor() + x_tensor.set_dims(self.x_np_data.shape) + x_tensor.set(self.x_np_data, place) - w = scope.new_var("W") - w_tensor = w.get_tensor() - w_tensor.set_dims([784, 100]) - w_tensor.alloc_float(place) - - w_tensor.set(numpy.random.random((784, 100)).astype("float32"), place) - - # Set a real numpy array here. - # x_tensor.set(numpy.array([])) + W_tensor = scope.new_var("W").get_tensor() + W_tensor.set_dims(self.W_np_data.shape) + W_tensor.set(self.W_np_data, place) op = Operator("fc", X="X", Y="Y", W="W") @@ -30,15 +26,20 @@ class TestFc(unittest.TestCase): if scope.find_var(out) is None: scope.new_var(out).get_tensor() - tensor = scope.find_var("Y").get_tensor() + Y_tensor = scope.find_var("Y").get_tensor() op.infer_shape(scope) - self.assertEqual([1000, 100], tensor.shape()) + self.assertEqual([1000, 100], Y_tensor.shape()) ctx = core.DeviceContext.create(place) op.run(scope, ctx) - # After complete all ops, check Y is expect or not. + py_data = np.matmul(self.x_np_data, self.W_np_data) + op_data = np.array(Y_tensor) + print py_data - op_data + self.assertTrue(np.allclose(py_data, op_data)) + + if __name__ == '__main__': diff --git a/python/paddle/v2/framework/tests/test_recurrent_op.py b/python/paddle/v2/framework/tests/test_recurrent_op.py index bab04d7a6cf..2ac9f86edb9 100644 --- a/python/paddle/v2/framework/tests/test_recurrent_op.py +++ b/python/paddle/v2/framework/tests/test_recurrent_op.py @@ -6,8 +6,7 @@ from paddle.v2.framework.op import Operator def py_sigmoid(x): - return 1. / (1 + np.exp(-x)) - + return 1. / (1. + np.exp(-x)) class PySimpleRNN(object): ''' @@ -62,10 +61,10 @@ class PySimpleRNNTest(unittest.TestCase): print 'output', output -def create_tensor(scope, name, shape): +def create_tensor(scope, name, shape, np_data): tensor = scope.new_var(name).get_tensor() tensor.set_dims(shape) - tensor.set(np.random.random(shape), core.CPUPlace()) + tensor.set(np_data, core.CPUPlace()) return tensor @@ -91,25 +90,36 @@ class TestRecurrentOp(unittest.TestCase): weight_dim = 15 sent_len = 11 - def forward(self): + def setUp(self): + self.py_rnn = PySimpleRNN(self.input_dim, + self.batch_size, + self.weight_dim, + self.sent_len) - self.scope = core.Scope() + def forward(self): + self.scope = core.Scope() self.create_global_variables() self.create_step_net() rnn_op = self.create_rnn_op() ctx = core.DeviceContext.create(core.CPUPlace()) - print 'infer_shape' rnn_op.infer_shape(self.scope) rnn_op.run(self.scope, ctx) + return np.array(self.scope.find_var("h").get_tensor()) def create_global_variables(self): # create inlink + x_np_data = self.py_rnn.x create_tensor(self.scope, "x", - [self.sent_len, self.batch_size, self.input_dim]) - create_tensor(self.scope, "W", [self.input_dim, self.input_dim]) - create_tensor(self.scope, "U", [self.input_dim, self.input_dim]) - create_tensor(self.scope, "h_boot", [self.batch_size, self.input_dim]) + [self.sent_len, self.batch_size, self.input_dim], x_np_data) + W_np_data = self.py_rnn.W + create_tensor(self.scope, "W", [self.input_dim, self.input_dim], W_np_data) + + U_np_data = self.py_rnn.U + create_tensor(self.scope, "U", [self.input_dim, self.input_dim], U_np_data) + + h_boot_np_data = self.py_rnn.h_boot + create_tensor(self.scope, "h_boot", [self.batch_size, self.input_dim], h_boot_np_data) self.scope.new_var("step_scopes") self.scope.new_var("h@alias") self.scope.new_var("h") @@ -146,8 +156,12 @@ class TestRecurrentOp(unittest.TestCase): def test_forward(self): print 'test recurrent op forward' - self.forward() - + pd_output = self.forward() + py_output = self.py_rnn.forward() + print 'pd_output', pd_output + print + print 'py_output', py_output + self.assertEqual(pd_output.shape, py_output.shape) if __name__ == '__main__': unittest.main() -- GitLab