Feature/remove g program (#5930)

* Unify fluid submodules to fluid module

Change books just use `import fluid`, not submodules

* Remove g_main_program/g_startup_program

Use default_main_program/default_startup_program instead

* Typo

* Fix CI

python/paddle/v2/fluid/evaluator.py

@@ -26,9 +26,9 @@ class Evaluator(object):
         name(str): The name of evaluator. such as, "accuracy". Used for generate 
             temporary variable name.
         main_program(Program, optional): The evaluator should be added to this 
-            main_program. Default g_main_program 
+            main_program. Default default_main_program()
         startup_program(Program, optional):The parameter should be added to this 
-            startup_program. Default g_startup_program
+            startup_program. Default default_startup_program()
             
     Attributes:
         states(list): The list of state variables. states will be reset to zero 

python/paddle/v2/fluid/executor.py

 import numpy as np
 from . import core
-from framework import Program, g_main_program
+from framework import Program, default_main_program
 
 __all__ = ['Executor', 'g_scope']
 
@@ -103,7 +103,7 @@ class Executor(object):
             fetch_list = []
 
         if program is None:
-            program = g_main_program
+            program = default_main_program()
 
         if not isinstance(program, Program):
             raise TypeError()

python/paddle/v2/fluid/framework.py

@@ -6,7 +6,7 @@ import proto.framework_pb2 as framework_pb2
 
 __all__ = [
     'Block', 'Variable', 'Program', 'Operator', 'default_startup_program',
-    'default_main_program', 'g_startup_program', 'g_main_program'
+    'default_main_program'
 ]
 
 
@@ -654,13 +654,13 @@ class Parameter(Variable):
 
 
 # program is a global instance.
-g_main_program = Program()
-g_startup_program = Program()
+_main_program_ = Program()
+_startup_program_ = Program()
 
 
 def default_startup_program():
-    return g_startup_program
+    return _startup_program_
 
 
 def default_main_program():
-    return g_main_program
+    return _main_program_

python/paddle/v2/fluid/io.py

 import os
 import cPickle as pickle
 
-from paddle.v2.fluid.framework import Program, Parameter, g_main_program, \
-    Variable
+from paddle.v2.fluid.framework import Program, Parameter, default_main_program, Variable
 
 __all__ = [
     'save_vars', 'save_params', 'save_persistables', 'load_vars', 'load_params',
@@ -46,7 +45,7 @@ def save_vars(executor, dirname, main_program=None, vars=None, predicate=None):
     """
     if vars is None:
         if main_program is None:
-            main_program = g_main_program
+            main_program = default_main_program()
         if not isinstance(main_program, Program):
             raise TypeError("program should be as Program type or None")
 
@@ -98,7 +97,7 @@ def load_vars(executor, dirname, main_program=None, vars=None, predicate=None):
     :param executor: executor that save variable
     :param dirname: directory path
     :param main_program: program. If vars is None, then filter all variables in this
-    program which fit `predicate`. Default g_program.
+    program which fit `predicate`. Default default_main_program().
     :param predicate: The Predicate describes a callable that returns a variable
     as a bool. If it returns true, the variables will be loaded.
     :param vars: variables need to be loaded. If specify vars, program &
@@ -107,7 +106,7 @@ def load_vars(executor, dirname, main_program=None, vars=None, predicate=None):
     """
     if vars is None:
         if main_program is None:
-            main_program = g_main_program
+            main_program = default_main_program()
         if not isinstance(main_program, Program):
             raise TypeError("program's type should be Program")
 
@@ -154,7 +153,7 @@ def load_persistables(executor, dirname, main_program=None):
 
 def get_inference_program(target_vars, main_program=None):
     if main_program is None:
-        main_program = g_main_program
+        main_program = default_main_program()
     if not isinstance(target_vars, list):
         target_vars = [target_vars]
 
@@ -177,12 +176,12 @@ def save_inference_model(dirname,
     :param target_vars: Variables from which we can get inference results.
     :param executor: executor that save inference model
     :param main_program: original program, which will be pruned to build the inference model.
-    Default g_main_program.
+            Default default_main_program().
 
     :return: None
     """
     if main_program is None:
-        main_program = g_main_program
+        main_program = default_main_program()
     if not isinstance(target_vars, list):
         target_vars = [target_vars]
 
@@ -272,10 +271,10 @@ def get_parameter_value_by_name(name, executor, program=None):
     :param executor: executor for retrieving the value
     :param name: the name of the parameter
     :param program: the program where the variable is found
-    Default g_main_program.
+            Default default_main_program().
     :return: the LoDTensor for the variable
     """
     if program is None:
-        program = g_main_program
+        program = default_main_program()
     var = program.global_block().var(name)
     return get_parameter_value(var, executor)

python/paddle/v2/fluid/layer_helper.py

 import copy
 import itertools
 
-from framework import Variable, g_main_program, \
-    g_startup_program, unique_name, dtype_is_floating
+from framework import Variable, default_main_program, default_startup_program, unique_name, dtype_is_floating
 from paddle.v2.fluid.initializer import Constant, Xavier
 
 
@@ -22,7 +21,7 @@ class LayerHelper(object):
     def main_program(self):
         prog = self.kwargs.get('main_program', None)
         if prog is None:
-            return g_main_program
+            return default_main_program()
         else:
             return prog
 
@@ -30,7 +29,7 @@ class LayerHelper(object):
     def startup_program(self):
         prog = self.kwargs.get('startup_program', None)
         if prog is None:
-            return g_startup_program
+            return default_startup_program()
         else:
             return prog
 

python/paddle/v2/fluid/layers.py

-from . import core
+import core
 import proto.framework_pb2 as framework_pb2
 from framework import OpProtoHolder, Variable, Program, Operator
 from initializer import Constant, Normal, Xavier

python/paddle/v2/fluid/tests/test_array_read_write_op.py

@@ -3,7 +3,7 @@ import paddle.v2.fluid.core as core
 import paddle.v2.fluid.layers as layers
 from paddle.v2.fluid.executor import Executor
 from paddle.v2.fluid.backward import append_backward_ops
-from paddle.v2.fluid.framework import g_main_program
+from paddle.v2.fluid.framework import default_main_program
 import numpy
 
 
@@ -66,7 +66,7 @@ class TestArrayReadWrite(unittest.TestCase):
 
         append_backward_ops(total_sum_scaled)
 
-        g_vars = map(g_main_program.global_block().var,
+        g_vars = map(default_main_program().global_block().var,
                      [each_x.name + "@GRAD" for each_x in x])
         g_out = [
             item.sum()

python/paddle/v2/fluid/tests/test_conditional_block.py

 import unittest
 import paddle.v2.fluid.layers as layers
 import paddle.v2.fluid.core as core
-from paddle.v2.fluid.framework import g_startup_program, g_main_program
+from paddle.v2.fluid.framework import default_startup_program, default_main_program
 from paddle.v2.fluid.executor import Executor
 from paddle.v2.fluid.backward import append_backward_ops
 import numpy
@@ -19,7 +19,7 @@ class ConditionalBlock(unittest.TestCase):
 
         cpu = core.CPUPlace()
         exe = Executor(cpu)
-        exe.run(g_startup_program)
+        exe.run(default_startup_program())
 
         x = numpy.random.random(size=(10, 1)).astype('float32')
 
@@ -29,7 +29,9 @@ class ConditionalBlock(unittest.TestCase):
         append_backward_ops(loss=loss)
         outs = exe.run(
             feed={'X': x},
-            fetch_list=[g_main_program.block(0).var(data.name + "@GRAD")])[0]
+            fetch_list=[
+                default_main_program().block(0).var(data.name + "@GRAD")
+            ])[0]
         print outs
 
 

python/paddle/v2/fluid/tests/test_executor_and_mul.py

 import unittest
-from paddle.v2.fluid.layers import mul, data, sequence_pool
+
+import numpy
 import paddle.v2.fluid.core as core
+
 from paddle.v2.fluid.executor import Executor
-from paddle.v2.fluid.framework import g_main_program
-import numpy
+from paddle.v2.fluid.layers import mul, data
 
 
 class TestExecutor(unittest.TestCase):
@@ -19,10 +20,7 @@ class TestExecutor(unittest.TestCase):
         a_np = numpy.random.random((100, 784)).astype('float32')
         b_np = numpy.random.random((784, 100)).astype('float32')
         exe = Executor(place)
-        outs = exe.run(g_main_program,
-                       feed={'a': a_np,
-                             'b': b_np},
-                       fetch_list=[out])
+        outs = exe.run(feed={'a': a_np, 'b': b_np}, fetch_list=[out])
         out = outs[0]
         self.assertEqual((100, 100), out.shape)
         self.assertTrue(numpy.allclose(out, numpy.dot(a_np, b_np)))

python/paddle/v2/fluid/tests/test_lod_rank_table.py

 from paddle.v2.fluid.layers import lod_rank_table, data
 from paddle.v2.fluid.executor import Executor
-from paddle.v2.fluid.framework import g_main_program
 import paddle.v2.fluid.core as core
 import numpy
 import unittest
@@ -18,7 +17,7 @@ class TestLoDRankTable(unittest.TestCase):
         tensor = core.LoDTensor()
         tensor.set(numpy.random.random(size=(17, 100)), cpu)
         tensor.set_lod([[0, 1, 3], [0, 5, 6, 7], [0, 3, 4, 9, 10, 13, 16, 17]])
-        exe.run(g_main_program, scope=scope, feed={'x': tensor})
+        exe.run(scope=scope, feed={'x': tensor})
         var = scope.find_var(rank_table.name)
         table = var.get_lod_rank_table()
         self.assertEqual([(0, 5), (1, 1), (2, 1)], table.items())

python/paddle/v2/fluid/tests/test_operator_desc.py

 import unittest
-from paddle.v2.fluid.framework import Variable, Program, g_main_program
+
 import paddle.v2.fluid.core as core
 
+from paddle.v2.fluid.framework import Program, default_startup_program
+
+main_program = default_startup_program()
+
 
 class TestOperator(unittest.TestCase):
     def test_error_type(self):
-        block = g_main_program.create_block()
+        block = main_program.create_block()
         try:
             block.append_op()
             self.assertFail()

python/paddle/v2/fluid/tests/test_parameter.py

 import unittest
-from paddle.v2.fluid.framework import g_main_program
+from paddle.v2.fluid.framework import default_main_program
 import paddle.v2.fluid.core as core
 from paddle.v2.fluid.executor import Executor
 import paddle.v2.fluid.io as io
 from paddle.v2.fluid.initializer import ConstantInitializer
 import numpy as np
 
+main_program = default_main_program()
+
 
 class TestParameter(unittest.TestCase):
     def test_param(self):
         shape = [784, 100]
         val = 1.0625
-        b = g_main_program.global_block()
+        b = main_program.global_block()
         param = b.create_parameter(
             name='fc.w',
             shape=shape,
@@ -23,9 +25,9 @@ class TestParameter(unittest.TestCase):
         self.assertEqual(core.DataType.FP32, param.dtype)
         self.assertEqual(0, param.block.idx)
         exe = Executor(core.CPUPlace())
-        p = exe.run(g_main_program, fetch_list=[param])[0]
+        p = exe.run(main_program, fetch_list=[param])[0]
         self.assertTrue(np.allclose(p, np.ones(shape) * val))
-        p = io.get_parameter_value_by_name('fc.w', exe, g_main_program)
+        p = io.get_parameter_value_by_name('fc.w', exe, main_program)
         self.assertTrue(np.allclose(np.array(p), np.ones(shape) * val))
 
 

python/paddle/v2/fluid/tests/test_program.py

 from __future__ import print_function
 import unittest
 
-from paddle.v2.fluid.framework import Program
-from paddle.v2.fluid.framework import g_main_program
+from paddle.v2.fluid.framework import Program, default_main_program
 import paddle.v2.fluid.layers as layers
 
+main_program = default_main_program()
+
 
 class TestProgram(unittest.TestCase):
     def test_program(self):
-        b = g_main_program.current_block()
+        b = main_program.current_block()
         self.assertEqual(-1, b.parent_idx)
         self.assertEqual(0, b.idx)
 
-        b = g_main_program.create_block()
+        b = main_program.create_block()
         self.assertEqual(1, b.idx)
         self.assertEqual(0, b.parent_idx)
 
-        b = g_main_program.create_block()
+        b = main_program.create_block()
         self.assertEqual(2, b.idx)
         self.assertEqual(1, b.parent_idx)
 
-        g_main_program.rollback()
+        main_program.rollback()
 
-        b = g_main_program.current_block()
+        b = main_program.current_block()
         self.assertEqual(1, b.idx)
         self.assertEqual(0, b.parent_idx)
 
-        b = g_main_program.create_block()
+        b = main_program.create_block()
         self.assertEqual(3, b.idx)
         self.assertEqual(1, b.parent_idx)
 
-        g_main_program.rollback()
-        b = g_main_program.current_block()
+        main_program.rollback()
+        b = main_program.current_block()
         self.assertEqual(1, b.idx)
         self.assertEqual(0, b.parent_idx)
 

python/paddle/v2/fluid/tests/test_shrink_rnn_memory.py

@@ -3,9 +3,11 @@ import paddle.v2.fluid.core as core
 from paddle.v2.fluid.executor import Executor
 import paddle.v2.fluid.layers as layers
 from paddle.v2.fluid.backward import append_backward_ops
-from paddle.v2.fluid.framework import g_main_program
+from paddle.v2.fluid.framework import default_main_program
 import numpy
 
+main_program = default_main_program()
+
 
 class TestShrinkRNNMemory(unittest.TestCase):
     def test_shrink_rnn_memory(self):
@@ -36,7 +38,7 @@ class TestShrinkRNNMemory(unittest.TestCase):
         append_backward_ops(loss=mem3_mean)
         x_grad = exe.run(
             feed={'x': tensor},
-            fetch_list=[g_main_program.global_block().var('x@GRAD')])[0]
+            fetch_list=[main_program.global_block().var('x@GRAD')])[0]
         self.assertAlmostEqual(1.0, x_grad.sum(), delta=0.1)
 
 

python/paddle/v2/fluid/tests/test_variable.py

 import unittest
-from paddle.v2.fluid.framework import g_main_program, Program, convert_np_dtype_to_dtype_
+from paddle.v2.fluid.framework import default_main_program, Program, convert_np_dtype_to_dtype_
 import paddle.v2.fluid.core as core
 import numpy as np
 
@@ -18,7 +18,7 @@ class TestVariable(unittest.TestCase):
         self.assertRaises(ValueError, lambda: convert("int8"))
 
     def test_var(self):
-        b = g_main_program.current_block()
+        b = default_main_program().current_block()
         w = b.create_var(
             dtype="float64", shape=[784, 100], lod_level=0, name="fc.w")
         self.assertNotEqual(str(w), "")