remove init_on_cpu and force_init_on_cpu APIs, test=develop (#22202)

python/paddle/fluid/initializer.py

@@ -24,56 +24,11 @@ from . import unique_name
 
 __all__ = [
     'Constant', 'Uniform', 'Normal', 'TruncatedNormal', 'Xavier', 'Bilinear',
-    'MSRA', 'force_init_on_cpu', 'init_on_cpu', 'ConstantInitializer',
-    'UniformInitializer', 'NormalInitializer', 'TruncatedNormalInitializer',
-    'XavierInitializer', 'BilinearInitializer', 'MSRAInitializer',
-    'NumpyArrayInitializer'
+    'MSRA', 'ConstantInitializer', 'UniformInitializer', 'NormalInitializer',
+    'TruncatedNormalInitializer', 'XavierInitializer', 'BilinearInitializer',
+    'MSRAInitializer', 'NumpyArrayInitializer'
 ]
 
-_force_init_on_cpu_ = False
-
-
-def force_init_on_cpu():
-    """
-    The flag of whether force to init variables on CPU.
-
-    Returns:
-        bool: the state if we should force init on CPU.
-
-    Examples:
-
-        .. code-block:: python
-
-            import paddle.fluid as fluid
-            if fluid.initializer.force_init_on_cpu():
-                step = fluid.layers.create_global_var(
-                    shape=[2,3], value=1.0, dtype='float32')
-
-    """
-    return _force_init_on_cpu_
-
-
-@signature_safe_contextmanager
-def init_on_cpu():
-    """
-    Force the variable to be inited on CPU.
-
-    Examples:
-        .. code-block:: python
-
-            import paddle.fluid as fluid
-            with fluid.initializer.init_on_cpu():
-                step = fluid.layers.create_global_var(
-                    shape=[2,3], value=1.0, dtype='float32')
-
-    """
-    global _force_init_on_cpu_
-
-    pre_state = force_init_on_cpu()
-    _force_init_on_cpu_ = True
-    yield
-    _force_init_on_cpu_ = pre_state
-
 
 class Initializer(object):
     """Base class for variable initializers
@@ -186,7 +141,7 @@ class ConstantInitializer(Initializer):
                 "shape": var.shape,
                 "dtype": int(out_dtype),
                 "value": float(self._value),
-                'force_cpu': self._force_cpu or force_init_on_cpu()
+                'force_cpu': self._force_cpu
             },
             stop_gradient=True)
 

python/paddle/fluid/layers/learning_rate_scheduler.py

@@ -29,7 +29,6 @@ from . import control_flow
 from . import nn
 from . import ops
 from . import tensor
-from ..initializer import init_on_cpu
 from ..framework import default_main_program, Parameter, unique_name, name_scope
 from ..framework import Variable
 from ..framework import in_dygraph_mode

python/paddle/fluid/layers/math_op_patch.py

@@ -17,7 +17,6 @@ from __future__ import print_function
 from .. import core
 from ..framework import Variable, unique_name
 from .layer_function_generator import OpProtoHolder
-from ..initializer import force_init_on_cpu
 
 _supported_int_dtype_ = [
     core.VarDesc.VarType.UINT8,
@@ -58,7 +57,7 @@ def monkey_patch_variable():
                 'dtype': var.dtype,
                 'shape': shape,
                 'value': value,
-                'force_cpu': force_init_on_cpu()
+                'force_cpu': False
             },
             stop_gradient=True)
         var.stop_gradient = True

python/paddle/fluid/layers/tensor.py

@@ -18,7 +18,7 @@ from ..layer_helper import LayerHelper
 from ..param_attr import ParamAttr
 from ..framework import convert_np_dtype_to_dtype_, in_dygraph_mode, _varbase_creator
 from ..framework import Variable
-from ..initializer import Constant, force_init_on_cpu
+from ..initializer import Constant
 from ..core import VarDesc
 from .. import core
 from .layer_function_generator import templatedoc
@@ -569,10 +569,7 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None):
           shape = fluid.layers.fill_constant([1,2], "int32", 2) # shape=[2,2]
           data4 = fluid.layers.fill_constant(shape=shape, dtype='bool', value=True) # data4=[[True,True],[True,True]]
     """
-    attrs = {
-        'value': float(value),
-        'force_cpu': force_cpu or force_init_on_cpu()
-    }
+    attrs = {'value': float(value), 'force_cpu': force_cpu}
 
     if convert_dtype(dtype) in ['int64', 'int32']:
         attrs['str_value'] = str(int(value))
@@ -601,10 +598,7 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None):
                 'fill_constant')
     check_type(shape, 'shape', (Variable, list, tuple), 'fill_constant')
     inputs = {}
-    attrs = {
-        'value': float(value),
-        'force_cpu': force_cpu or force_init_on_cpu()
-    }
+    attrs = {'value': float(value), 'force_cpu': force_cpu}
 
     if convert_dtype(dtype) in ['int64', 'int32']:
         attrs['str_value'] = str(int(value))
@@ -722,7 +716,7 @@ def fill_constant_batch_size_like(input,
         'value': float(value),
         'input_dim_idx': input_dim_idx,
         'output_dim_idx': output_dim_idx,
-        'force_cpu': force_cpu or force_init_on_cpu()
+        'force_cpu': force_cpu
     }
     if convert_dtype(dtype) in ['int64', 'int32']:
         attrs['str_value'] = str(int(value))

python/paddle/fluid/tests/unittests/seresnext_net.py

@@ -17,7 +17,6 @@ import paddle.fluid as fluid
 fluid.core._set_eager_deletion_mode(-1, -1, False)
 
 import paddle.fluid.layers.ops as ops
-from paddle.fluid.initializer import init_on_cpu
 from paddle.fluid.layers.learning_rate_scheduler import cosine_decay
 from simple_nets import init_data
 import math