From b0c75f1763994012b7f12a3afe0a9df42d0917c6 Mon Sep 17 00:00:00 2001 From: xuezhong Date: Wed, 30 Jan 2019 12:30:17 +0000 Subject: [PATCH] remove debug print --- paddle/fluid/operators/lstmp_op.h | 1 - .../fluid/tests/unittests/test_lstmp_op.py | 80 ------------------- 2 files changed, 81 deletions(-) diff --git a/paddle/fluid/operators/lstmp_op.h b/paddle/fluid/operators/lstmp_op.h index 8424aa872..9cad0bfd0 100644 --- a/paddle/fluid/operators/lstmp_op.h +++ b/paddle/fluid/operators/lstmp_op.h @@ -225,7 +225,6 @@ class LSTMPKernel : public framework::OpKernel { // Since the batch computing for LSTMP reorders the input sequence // according to their length. The initialized hidden state also needs // to reorder. - VLOG(1) << "qxz h0 used"; ReorderInitState(device_ctx, *hidden_t0, order, &ordered_h0, true); blas.MatMul(ordered_h0, false, *weight, false, static_cast(1.0), diff --git a/python/paddle/fluid/tests/unittests/test_lstmp_op.py b/python/paddle/fluid/tests/unittests/test_lstmp_op.py index 98252f86c..299a8c969 100644 --- a/python/paddle/fluid/tests/unittests/test_lstmp_op.py +++ b/python/paddle/fluid/tests/unittests/test_lstmp_op.py @@ -44,7 +44,6 @@ def lstmp( act_proj=None): def _step(x, w_r, w_rh, w_c, r_pre, c_pre, proj_clip, cell_clip, act_gate, act_cell, act_cand, act_proj): - #import pdb; pdb.set_trace() g = np.dot(r_pre, w_r) # 1 x 4D g = g + x g = np.reshape(g, (1, g.size)) @@ -59,9 +58,6 @@ def lstmp( c = g_f * c_pre + g_i * act_cand(c) # 1 x D def array_clip(a, clip): - #print('clip:{}'.format(clip)) - #print('old' + str(a)) - size = np.prod(a.shape) new_a = np.reshape(a, (size)) for i in range(size): @@ -134,92 +130,17 @@ class TestLstmpOp(LstmTest.TestLstmOp): def reset_argument(self): pass - def setUp2(self): - self.set_argument() - # projection size - self.P = 2 - - self.reset_argument() - self.op_type = 'lstmp' - self.act_proj = 'identity' - self.use_peepholes = False - self.has_initial_state = True - self.lod = [[5]] - - T = sum(self.lod[0]) - N = len(self.lod[0]) - - proj_clip = 0.5 - cell_clip = 0.0 - - #import pdb; pdb.set_trace() - x=np.array([[-0.50806344, 0.50909436], \ - [-0.50087136, 0.4904187 ], \ - [-0.48933774, 0.50408053], \ - [ 0.00896523, 0.00770854], \ - [-0.00851139,-0.01005108]]) - wx = np.array([[ 0.2932311, -0.8829277, 1.100133, 0.8197811, -0.8194872, -0.829262, 0.7708865, -0.62339246, -0.7656475, 0.4283645, -0.27164033, -0.3600223 ], \ - [-0.609142, 0.25025278, 0.15731744, -0.66051376, -0.70994514, 0.8344964, -0.00551117, -0.7072167, -0.63929003, -0.52340907, -0.8842589, 0.9531688 ]]) - x = np.dot(x, wx) - - w = np.array([[ 0.7808204, -0.7412322, -0.9458036, -0.01664658, 0.7930616, 0.10208707, 0.20036687, -0.16743736, 1.0295134, -0.3118722, 0.02241168, 0.3154219 ], \ - [-0.29026014, 0.24638331, -0.5435432, 0.87635124, -0.96091515, -0.1411362, 0.58606523, -0.38996056, -0.9003789, 0.8540163, -0.8831781, -0.28499633]]) - - w_rh = np.array([[0.15685119, 0.05694652], [-0.9641068, -1.5106804], - [0.3599193, 1.2540514]]) - w_b = np.array([[ - -0.49999997, 0.5, -0.49999997, -0.5, 0.5, 0.5, 0.49999997, - -0.49999997, 0.49999997, -0.5, 0.49999997, 0.5 - ]]) - h0 = np.array([[-1.3392334e-04, -6.8468950e-04]]) - c0 = np.array([[4.5552300e-04, 1.3302206e-03, -3.6721351e-04]]) - w_c = None - self.lod = [[5]] - #import pdb; pdb.set_trace() - r, c = lstmp(x, self.lod, h0, c0, w, w_rh, w_b, w_c, self.is_reverse, - proj_clip, cell_clip, ACTIVATION[self.act_gate], - ACTIVATION[self.act_cell], ACTIVATION[self.act_cand], - ACTIVATION[self.act_proj]) - self.inputs = {'Input': (x, self.lod), 'Weight': w, 'ProjWeight': w_rh} - - self.inputs['Bias'] = w_b - - if self.has_initial_state: - self.inputs['H0'] = h0 - self.inputs['C0'] = c0 - - self.outputs = { - 'Projection': (r, self.lod), - 'Cell': (c, self.lod), - } - self.attrs = { - 'use_peepholes': self.use_peepholes, - 'is_reverse': self.is_reverse, - 'proj_clip': proj_clip, - 'cell_clip': cell_clip, - 'gate_activation': self.act_gate, - 'cell_activation': self.act_cell, - 'candidate_activation': self.act_cand, - 'proj_activation': self.act_proj - } - def setUp(self): self.set_argument() # projection size self.P = 10 - #self.D = 9 self.act_proj = self.act_cell self.reset_argument() self.op_type = 'lstmp' - #self.use_peepholes=False - #self.lod=[[7]] - #self.act_proj='identity' - #self.act_proj='tanh' T = sum(self.lod[0]) N = len(self.lod[0]) - #np.random.seed=123 x = np.random.normal(size=(T, 4 * self.D)).astype('float64') if self.has_initial_state: h0 = np.random.normal(size=(N, self.P)).astype('float64') @@ -238,7 +159,6 @@ class TestLstmpOp(LstmTest.TestLstmOp): w_rh = np.random.normal(size=(self.D, self.P)).astype('float64') proj_clip = 0.1 cell_clip = 0.1 - #import pdb; pdb.set_trace() r, c = lstmp(x, self.lod, h0, c0, w, w_rh, w_b, w_c, self.is_reverse, proj_clip, cell_clip, ACTIVATION[self.act_gate], ACTIVATION[self.act_cell], ACTIVATION[self.act_cand], -- GitLab