remove init_on_cpu from models (#4164)

PaddleCV/icnet/eval.py

@@ -16,7 +16,6 @@ import paddle.fluid as fluid
 import numpy as np
 from utils import add_arguments, print_arguments, get_feeder_data, check_gpu
 from paddle.fluid.layers.learning_rate_scheduler import _decay_step_counter
-from paddle.fluid.initializer import init_on_cpu
 from icnet import icnet
 import cityscape
 import argparse

PaddleCV/icnet/infer.py

@@ -25,7 +25,6 @@ import paddle
 from icnet import icnet
 from utils import add_arguments, print_arguments, get_feeder_data, check_gpu
 from paddle.fluid.layers.learning_rate_scheduler import _decay_step_counter
-from paddle.fluid.initializer import init_on_cpu
 import numpy as np
 
 IMG_MEAN = np.array((103.939, 116.779, 123.68), dtype=np.float32)

PaddleCV/icnet/train.py

@@ -26,7 +26,6 @@ import paddle.fluid as fluid
 import numpy as np
 from utils import add_arguments, print_arguments, get_feeder_data, check_gpu
 from paddle.fluid.layers.learning_rate_scheduler import _decay_step_counter
-from paddle.fluid.initializer import init_on_cpu
 
 if 'ce_mode' in os.environ:
     np.random.seed(10)
@@ -71,7 +70,6 @@ def create_loss(predict, label, mask, num_classes):
 
 def poly_decay():
     global_step = _decay_step_counter()
-    with init_on_cpu():
     decayed_lr = LEARNING_RATE * (fluid.layers.pow(
         (1 - global_step / TOTAL_STEP), POWER))
     return decayed_lr

PaddleCV/image_classification/utils/optimizer.py

@@ -20,7 +20,6 @@ import math
 
 import paddle.fluid as fluid
 import paddle.fluid.layers.ops as ops
-from paddle.fluid.initializer import init_on_cpu
 from paddle.fluid.layers.learning_rate_scheduler import _decay_step_counter
 
 
@@ -30,10 +29,9 @@ def cosine_decay(learning_rate, step_each_epoch, epochs=120):
     """
     global_step = _decay_step_counter()
 
-    with init_on_cpu():
     epoch = ops.floor(global_step / step_each_epoch)
     decayed_lr = learning_rate * \
-                     (ops.cos(epoch * (math.pi / epochs)) + 1)/2
+                v(ops.cos(epoch * (math.pi / epochs)) + 1)/2
     return decayed_lr
 
 
@@ -53,7 +51,6 @@ def cosine_decay_with_warmup(learning_rate, step_each_epoch, epochs=120):
     warmup_epoch = fluid.layers.fill_constant(
         shape=[1], dtype='float32', value=float(5), force_cpu=True)
 
-    with init_on_cpu():
     epoch = ops.floor(global_step / step_each_epoch)
     with fluid.layers.control_flow.Switch() as switch:
         with switch.case(epoch < warmup_epoch):
@@ -80,7 +77,6 @@ def exponential_decay_with_warmup(learning_rate, step_each_epoch, decay_epochs,
     warmup_epoch = fluid.layers.fill_constant(
         shape=[1], dtype='float32', value=float(warm_up_epoch), force_cpu=True)
 
-    with init_on_cpu():
     epoch = ops.floor(global_step / step_each_epoch)
     with fluid.layers.control_flow.Switch() as switch:
         with switch.case(epoch < warmup_epoch):

PaddleCV/ocr_recognition/crnn_ctc_model.py

@@ -16,7 +16,6 @@ from __future__ import division
 from __future__ import print_function
 import paddle.fluid as fluid
 from paddle.fluid.layers.learning_rate_scheduler import _decay_step_counter
-from paddle.fluid.initializer import init_on_cpu
 import math
 import six