move get_test_program to non-layer io.py

python/paddle/fluid/io.py

@@ -17,7 +17,7 @@ import time
 import shutil
 
 from paddle.fluid.evaluator import Evaluator
-from paddle.fluid.framework import Program, Parameter, default_main_program, Variable
+from paddle.fluid.framework import Program, Parameter, default_main_program, default_startup_program, Variable
 from . import core
 
 __all__ = [
@@ -744,3 +744,101 @@ def get_latest_checkpoint_serial(checkpoint_dir):
         if success_num > current_dir:
             current_dir = success_num
     return current_dir
+
+
+def get_test_program(filelist, program=None, startup_program=None):
+    """
+    Transpile current train program to a program to read test dataset
+    if the program is using reader ops like "open_files_op".
+    """
+
+    def _copy_reader_var_(block, var, new_name=None):
+        if new_name == None:
+            new_name = var.name
+        new_var = block.create_var(
+            name=str(new_name), type=core.VarDesc.VarType.READER)
+        new_var.desc.set_shapes(var.desc.shapes())
+        new_var.desc.set_dtypes(var.desc.dtypes())
+        new_var.persistable = True
+        return new_var
+
+    def get_test_reader_name(train_reader_name):
+        return train_reader_name + "_test"
+
+    def is_reader_op(op):
+        block = op.block
+        if "Out" in op.output_names:
+            reader_out = block.vars[op.output("Out")[0]]
+            if reader_out.type == core.VarDesc.VarType.READER:
+                return True
+        return False
+
+    if program == None:
+        program = default_main_program()
+    if startup_program == None:
+        startup_program = default_startup_program()
+    startup_block = startup_program.global_block()
+
+    # 1. find out the orignal reader var name
+    startup_reader_op_list = []
+
+    for op in startup_block.ops:
+        if is_reader_op(op):
+            startup_reader_op_list.append(op)
+
+    if len(startup_reader_op_list) == 0:
+        return program
+
+    root_reader_op = startup_reader_op_list[0]
+    train_test_reader_map = {}
+    # 2. add operators to startup to read open and read test data files
+    for op in startup_reader_op_list:
+        assert (len(op.output("Out")) == 1)
+        train_reader_name = op.output("Out")[0]
+        train_reader = startup_block.vars[train_reader_name]
+        test_reader = _copy_reader_var_(
+            startup_block,
+            train_reader,
+            new_name=get_test_reader_name(train_reader_name))
+        train_test_reader_map[train_reader.name] = test_reader
+
+        test_op_inputs = {}
+        for name in op.input_names:
+            train_arg_names = op.input(name)
+            test_arg_vars = []
+            for arg_name in train_arg_names:
+                arg_var = train_test_reader_map[
+                    arg_name] if name == "UnderlyingReader" else startup_block.vars[
+                        arg_name]
+                test_arg_vars.append(arg_var)
+            test_op_inputs[name] = test_arg_vars
+
+        test_op = startup_block.append_op(
+            type=op.type,
+            inputs=test_op_inputs,
+            outputs={'Out': [test_reader]},
+            attrs=op.attrs)
+        # root reader op's filelist attr for read test files
+        if op.type == root_reader_op.type:
+            test_op.set_attr("file_names", filelist)
+        if op.type == "create_multi_pass_reader":
+            test_op.set_attr("pass_num", 1)
+
+    # 3. rename reader vars in inference program to different name
+    #    to avoid read from train data.
+    main_block = program.global_block()
+    for var in main_block.vars.values():
+        if var.type == core.VarDesc.VarType.READER:
+            main_block.rename_var(
+                str(var.name), str(get_test_reader_name(var.name)))
+
+    for op in main_block.ops:
+        if op.type == root_reader_op.type:
+            test_op.set_attr("file_names", filelist)
+        if op.type == "create_multi_pass_reader":
+            test_op.set_attr("pass_num", 1)
+
+    startup_program.sync_with_cpp()
+    program.sync_with_cpp()
+
+    return program

python/paddle/fluid/layers/io.py

@@ -692,91 +692,3 @@ def load(out, file_path, load_as_fp16=None):
     if load_as_fp16 is not None:
         attrs['load_as_fp16'] = load_as_fp16
     helper.append_op(type="load", inputs={}, output={"Out": out}, args=attrs)
-
-
-def get_test_program(filelist, program=None, startup_program=None):
-    """
-    Transpile current train program to a program to read test dataset
-    if the program is using reader ops like "open_files_op".
-    """
-
-    def get_test_reader_name(train_reader_name):
-        return train_reader_name + "_test"
-
-    def is_reader_op(op):
-        block = op.block
-        if "Out" in op.output_names:
-            reader_out = block.vars[op.output("Out")[0]]
-            if reader_out.type == core.VarDesc.VarType.READER:
-                return True
-        return False
-
-    if program == None:
-        program = default_main_program()
-    if startup_program == None:
-        startup_program = default_startup_program()
-    startup_block = startup_program.global_block()
-
-    # 1. find out the orignal reader var name
-    startup_reader_op_list = []
-
-    for op in startup_block.ops:
-        if is_reader_op(op):
-            startup_reader_op_list.append(op)
-
-    if len(startup_reader_op_list) == 0:
-        return program
-
-    root_reader_op = startup_reader_op_list[0]
-    train_test_reader_map = {}
-    # 2. add operators to startup to read open and read test data files
-    for op in startup_reader_op_list:
-        assert (len(op.output("Out")) == 1)
-        train_reader_name = op.output("Out")[0]
-        train_reader = startup_block.vars[train_reader_name]
-        test_reader = _copy_reader_var_(
-            startup_block,
-            train_reader,
-            new_name=get_test_reader_name(train_reader_name))
-        train_test_reader_map[train_reader.name] = test_reader
-
-        test_op_inputs = {}
-        for name in op.input_names:
-            train_arg_names = op.input(name)
-            test_arg_vars = []
-            for arg_name in train_arg_names:
-                arg_var = train_test_reader_map[
-                    arg_name] if name == "UnderlyingReader" else startup_block.vars[
-                        arg_name]
-                test_arg_vars.append(arg_var)
-            test_op_inputs[name] = test_arg_vars
-
-        test_op = startup_block.append_op(
-            type=op.type,
-            inputs=test_op_inputs,
-            outputs={'Out': [test_reader]},
-            attrs=op.attrs)
-        # root reader op's filelist attr for read test files
-        if op.type == root_reader_op.type:
-            test_op.set_attr("file_names", filelist)
-        if op.type == "create_multi_pass_reader":
-            test_op.set_attr("pass_num", 1)
-
-    # 3. rename reader vars in inference program to different name
-    #    to avoid read from train data.
-    main_block = program.global_block()
-    for var in main_block.vars.values():
-        if var.type == core.VarDesc.VarType.READER:
-            main_block.rename_var(
-                str(var.name), str(get_test_reader_name(var.name)))
-
-    for op in main_block.ops:
-        if op.type == root_reader_op.type:
-            test_op.set_attr("file_names", filelist)
-        if op.type == "create_multi_pass_reader":
-            test_op.set_attr("pass_num", 1)
-
-    startup_program.sync_with_cpp()
-    program.sync_with_cpp()
-
-    return program