move python tools to tools python

.gitignore

@@ -92,3 +92,4 @@ metal/images/
 metal/paddle-mobile/paddle-mobile/CPU/libpaddle-mobile.a
 *.xcuserdatad/
 */xcuserdata/
+/venv/

tools/python/modeltools/.gitignore

+# Created by .ignore support plugin (hsz.mobi)
+### Python template
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+/yolo/datas/
+/mobilenet/datas/

python/tools/mdl2fluid/op_types.py → tools/python/modeltools/core/op_types.py

@@ -5,22 +5,28 @@ layer_mdl_conv = 'ConvolutionLayer'
 layer_mdl_deepwise_conv = 'DepthwiseConvolutionLayer'
 layer_mdl_relu = 'ReluLayer'
 layer_mdl_pointwise_add = 'PointwiseConvolutionLayer'
+layer_mdl_pooling = 'PoolingLayer'
+layer_mdl_softmax = 'SoftmaxLayer'
 
 # fluid ops
 op_fluid_fusion_conv_add = 'fusion_conv_add'
 op_fluid_relu = 'relu'
+op_fluid_pooling = 'pool2d'
+op_fluid_softmax = 'softmax'
 
 # dict mdk layer ---  fluid op
 mdl2fluid_op_layer_dict = {
     layer_mdl_conv: op_fluid_fusion_conv_add,
     layer_mdl_deepwise_conv: op_fluid_fusion_conv_add,
     layer_mdl_relu: op_fluid_relu,
-    layer_mdl_pointwise_add: op_fluid_fusion_conv_add
+    layer_mdl_pointwise_add: op_fluid_fusion_conv_add,
+    layer_mdl_pooling: op_fluid_pooling,
+    layer_mdl_softmax: op_fluid_softmax
 }
 
 mdl_outputs_key = "outputs"
 mdl_inputs_key = "inputs"
-mdl_weight_key = "weights"
+mdl_weight_key = "weight"
 mdl_attrs_key = "params"
 
 # dict of mdl-input _out param  to fluid input out attrs
@@ -39,13 +45,30 @@ fusion_conv_add_dict = {
 relu_dict = {
     mdl_inputs_key: 'X',
     mdl_outputs_key: 'Out',
-    mdl_weight_key: ()
+    # mdl_weight_key: ()
 
 }
+
+pool2d_dict = {
+    mdl_inputs_key: 'X',
+    mdl_outputs_key: 'Out',
+    # mdl_weight_key: (),
+    mdl_attrs_key: ('pooling_type', 'global_pooling')
+
+}
+
+softmax_dict = {
+    mdl_inputs_key: 'X',
+    mdl_outputs_key: 'Out',
+    mdl_weight_key: (),
+    mdl_attrs_key: ()
+}
 # mdl layers  ---  fluid ops
 op_io_dict = {
     'fusion_conv_add': fusion_conv_add_dict,
-    'relu': relu_dict
+    'relu': relu_dict,
+    'pool2d': pool2d_dict,
+    'softmax': softmax_dict
 }
 
 # fluid attr key  ---  mdl params key
@@ -60,64 +83,3 @@ fluid_attrs_type_dict = {
     'strides': 6,
     'groups': 6
 }
-
-# '': "bias_term",    是不是要add   目前 yolo的模型都是 bias_term = 1
-
-
-# attrs {
-#       name: "axis"
-#       type: INT
-#       i: 1
-#     }
-
-
-# attrs_name = {
-#     'name': "workspace_size_MB",
-#     'type': 'INT',
-#     'i': '4096'
-# }
-# attrs
-# {
-#     name: "data_format"
-#     type: STRING
-#     s: "AnyLayout"
-# }
-# attrs
-# {
-#     name: "use_mkldnn"
-#     type: BOOLEAN
-#     b: false
-# }
-# attrs
-# {
-#     name: "use_cudnn"
-#     type: BOOLEAN
-#     b: true
-# }
-# attrs
-# {
-#     name: "dilations"
-#     type: INTS
-#     ints: 1
-#     ints: 1
-# }
-# attrs
-# {
-#     name: "groups"
-#     type: INT
-#     i: 1
-# }
-# attrs
-# {
-#     name: "paddings"
-#     type: INTS
-#     ints: 0
-#     ints: 0
-# }
-# attrs
-# {
-#     name: "strides"
-#     type: INTS
-#     ints: 1
-#     ints: 1
-# }

tools/python/modeltools/mobilenet/converter_mobilenet.py

+import json
+import os
+
+from core import framework_pb2 as framework_pb2, op_types as types
+from mobilenet.swicher import Swichter
+import shutil
+
+
+def load_mdl(mdl_json_path):
+    # print('mdl json path : ' + mdl_json_path)
+    with open(mdl_json_path, 'r') as f:
+        return json.load(f)
+
+
+class Converter:
+    'convert mdlmodel to fluidmodel'
+
+    def __init__(self, base_dir, mdl_json_path):
+        self.mdl_json_path = base_dir + mdl_json_path
+        self.base_dir = base_dir
+        print mdl_json_path
+        self.mdl_json = load_mdl(self.mdl_json_path)
+        self.program_desc = framework_pb2.ProgramDesc()
+        self.weight_list_ = []
+        self.deepwise_weight_list_ = []
+        # print(json_dick)
+        # layers = (json_dick['layer'])
+        # for layer in layers:
+        #     print(layer)
+
+    def convert(self):
+        print 'convert begin.....'
+        # add block_desc
+        block_desc = self.program_desc.blocks.add()
+        block_desc.idx = 0
+        block_desc.parent_idx = -1
+        self.package_ops(block_desc)
+        self.package_vars(block_desc)
+        print 'blocks: '
+        print self.program_desc.blocks
+        print 'convert end.....'
+        desc_serialize_to_string = self.program_desc.SerializeToString()
+
+        outputmodel_ = self.base_dir + 'datas/target/outputmodel/'
+        if os.path.exists(outputmodel_):
+            shutil.rmtree(outputmodel_)
+        os.makedirs(outputmodel_, 0777)
+        # todo copy weight files
+        # if os.path.exists(outputmodel_):
+        #     shutil.rmtree(outputmodel_)
+        # shutil.copytree('yolo/datas/multiobjects/float32s_nchw_with_head/', 'mobilenet/datas/target/outputmodel/')
+
+        f = open(outputmodel_ + "__model__", "wb")
+        f.write(desc_serialize_to_string)
+        f.close()
+
+    def package_ops(self, block_desc):
+
+        self.add_op_feed(block_desc)
+
+        # add ops with layer
+        if 'layer' in self.mdl_json:
+
+            layers_ = self.mdl_json['layer']
+            for layer in layers_:
+                desc_ops_add = block_desc.ops.add()
+
+                # print layer
+                # for i in layer:
+                #     print i
+                if 'name' in layer:
+                    l_name = layer['name']
+                if 'type' in layer:
+                    self.package_ops_type(desc_ops_add, layer)
+
+                if 'weight' in layer:
+                    self.package_ops_weight2inputs(desc_ops_add, layer)
+
+                if 'output' in layer:
+                    self.package_ops_outputs(desc_ops_add, layer)
+
+                if 'input' in layer:
+                    self.package_ops_inputs(desc_ops_add, layer)
+
+                self.package_ops_attrs(desc_ops_add, layer)
+
+        self.add_op_fetch(block_desc)
+
+    def add_op_feed(self, block_desc):
+        desc_ops_add = block_desc.ops.add()
+        inputs_add = desc_ops_add.inputs.add()
+        inputs_add.parameter = 'X'
+        inputs_add.arguments.append('feed')
+        desc_ops_add.type = 'feed'
+        outputs_add = desc_ops_add.outputs.add()
+        outputs_add.parameter = 'Out'
+        outputs_add.arguments.append('data')
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'col'
+        # boolean
+        attrs_add.type = 0
+        attrs_add.i = 0
+
+    def add_op_fetch(self, block_desc):
+        desc_ops_add = block_desc.ops.add()
+        inputs_add = desc_ops_add.inputs.add()
+        inputs_add.parameter = 'X'
+        inputs_add.arguments.append('conv_pred_87')
+        desc_ops_add.type = 'fetch'
+        outputs_add = desc_ops_add.outputs.add()
+        outputs_add.parameter = 'Out'
+        outputs_add.arguments.append('fetch')
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'col'
+        # boolean
+        attrs_add.type = 0
+        attrs_add.i = 0
+
+    @staticmethod
+    def package_ops_attrs(desc_ops_add, layer):
+        # print l_params
+        # print desc_ops_add.type
+        if desc_ops_add.type == types.op_fluid_fusion_conv_add:
+            Converter.pack_fusion_conv_add_attr(desc_ops_add, layer)
+        elif desc_ops_add.type == types.op_fluid_relu:
+            # fusion_conv_add : attrs
+            attrs_add = desc_ops_add.attrs.add()
+            attrs_add.name = 'use_mkldnn'
+            # boolean
+            attrs_add.type = 6
+            attrs_add.b = 0
+
+    @staticmethod
+    def pack_fusion_conv_add_attr(desc_ops_add, layer):
+
+        # fusion_conv_add : attrs
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'workspace_size_MB'
+        # 0-->INT
+        attrs_add.type = 0
+        attrs_add.i = 4096
+
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'data_format'
+        # 2-->STRING
+        attrs_add.type = 2
+        attrs_add.s = 'AnyLayout'
+
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'use_mkldnn'
+        # boolean
+        attrs_add.type = 6
+        attrs_add.b = 0
+
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'use_cudnn'
+        # boolean
+        attrs_add.type = 6
+        attrs_add.b = 1
+
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'dilations'
+        # ints
+        attrs_add.type = 3
+        attrs_add.ints.append(1)
+        attrs_add.ints.append(1)
+
+        attrs_add = desc_ops_add.attrs.add()
+        attrs_add.name = 'axis'
+        # int
+        attrs_add.type = 0
+        attrs_add.i = 1
+
+        if 'param' in layer:
+            l_params = layer['param']
+
+            attrs_add = desc_ops_add.attrs.add()
+            attrs_add.name = 'paddings'
+            # ints
+            attrs_add.type = 3
+            attrs_add.ints.append(l_params[types.fusion_conv_add_attrs_dict.get('paddings')])
+            attrs_add.ints.append(l_params[types.fusion_conv_add_attrs_dict.get('paddings')])
+
+            attrs_add = desc_ops_add.attrs.add()
+            attrs_add.name = 'strides'
+            # ints
+            attrs_add.type = 3
+            attrs_add.ints.append(l_params[types.fusion_conv_add_attrs_dict.get('strides')])
+            attrs_add.ints.append(l_params[types.fusion_conv_add_attrs_dict.get('strides')])
+
+            attrs_add = desc_ops_add.attrs.add()
+            attrs_add.name = 'groups'
+            # int
+            attrs_add.type = 0
+            attrs_add.i = l_params[types.fusion_conv_add_attrs_dict.get('groups')]
+            # attrs_add.i = 1
+
+        #
+        # op_attrs_tupl = types.op_io_dict.get(desc_ops_add.type) \
+        #     .get(types.mdl_attrs_key)
+        #
+        #
+        #
+        #
+        # # group stride padding
+        # print '----------------------'
+        # for i, val in enumerate(op_attrs_tupl):
+        #     attrs_add = desc_ops_add.attrs.add()
+        #     attr_name = op_attrs_tupl[i]
+        #     print attr_name
+        #     attrs_add.name = attr_name
+        #     attrs_add.type = types.fluid_attrs_type_dict.get(attr_name)
+        #     attrs_add.
+        #     print l_params[types.fusion_conv_add_attrs_dict.get(attr_name)]
+
+        # for p in l_params:
+        #     attrs_add = desc_ops_add.attrs.add()
+
+    @staticmethod
+    def package_ops_inputs(desc_ops_add, layer):
+        l_inputs = layer['input']
+        for i in l_inputs:
+            inputs_add = desc_ops_add.inputs.add()
+            # print i
+            inputs_add.parameter = types.op_io_dict.get(desc_ops_add.type).get(types.mdl_inputs_key)
+            inputs_add.arguments.append(i)
+
+    @staticmethod
+    def package_ops_outputs(desc_ops_add, layer):
+        l_outputs = layer['output']
+        for o in l_outputs:
+            # print o
+            outputs_add = desc_ops_add.outputs.add()
+            dict = types.op_io_dict.get(desc_ops_add.type)
+            print 'desc_ops_add.type:  ' + desc_ops_add.type
+            print dict
+            outputs_add.parameter = dict.get(types.mdl_outputs_key)
+            outputs_add.arguments.append(o)
+
+    def package_ops_weight2inputs(self, desc_ops_add, layer):
+        l_weights = layer['weight']
+        for w in l_weights:
+            self.weight_list_.append(w)
+
+        if layer['type'] == types.layer_mdl_deepwise_conv:
+            # print l_weights[0]
+            self.deepwise_weight_list_.append(l_weights[0])
+
+        op_weight_tup = types.op_io_dict.get(desc_ops_add.type).get(types.mdl_weight_key)
+        if op_weight_tup is not None:
+            # print len(op_weight_tup)
+            for i, val in enumerate(op_weight_tup):
+                # print i
+                # print val
+                inputs_add = desc_ops_add.inputs.add()
+                inputs_add.parameter = op_weight_tup[i]
+                inputs_add.arguments.append(l_weights[i])
+
+        # for w in l_weights:
+        #     inputs_add = desc_ops_add.inputs.add()
+        #     # print w
+        #     inputs_add.parameter = op_weight_tup[0]
+        #     inputs_add.arguments.append(w)
+
+    @staticmethod
+    def package_ops_type(desc_ops_add, layer):
+        l_type = layer['type']
+        # print l_type
+        # print mdl2fluid_op_layer_dict.get(l_type)
+        desc_ops_add.type = types.mdl2fluid_op_layer_dict.get(l_type)
+
+    def package_vars(self, block_desc):
+        vars_add = block_desc.vars.add()
+        vars_add.name = 'feed'
+        vars_add.type.type = 9  # 9 is FEED_MINIBATCH
+        vars_add.persistable = 1
+        # fetch
+        vars_add = block_desc.vars.add()
+        vars_add.name = 'fetch'
+        vars_add.type.type = 10  # 10 is fetch list
+        vars_add.persistable = 1
+
+        json_matrix_ = self.mdl_json['matrix']
+        # print json_matrix_
+        for j in json_matrix_:
+            vars_add = block_desc.vars.add()
+            vars_add.name = j
+            vars_add.type.type = 7  # 7 is lodtensor
+            # print j
+            tensor = vars_add.type.lod_tensor.tensor
+            tensor.data_type = 5  # 5 is FP32
+
+            # print json_matrix_
+
+            dims_of_matrix = json_matrix_.get(j)
+            # dims_size = len(dims_of_matrix)
+            # print dims_size
+
+            # if dims_size == 4:
+            #     tensor.dims.append(dims_of_matrix[0])  # N
+            #     tensor.dims.append(dims_of_matrix[3])  # C
+            #     tensor.dims.append(dims_of_matrix[1])  # H
+            #     tensor.dims.append(dims_of_matrix[2])  # W
+            # else:
+
+            # issues in mdl model filter swich n and c
+            if j in self.deepwise_weight_list_ and len(dims_of_matrix) == 4:
+                print j
+                tensor.dims.append(dims_of_matrix[1])
+                tensor.dims.append(dims_of_matrix[0])
+                tensor.dims.append(dims_of_matrix[2])
+                tensor.dims.append(dims_of_matrix[3])
+                print tensor.dims
+            else:
+                for dims in dims_of_matrix:
+                    # print dims
+                    tensor.dims.append(dims)
+
+            if j in self.weight_list_:
+                vars_add.persistable = 1
+                dims_size = len(dims_of_matrix)
+                # print dims_size
+                # if dims_size == 4:
+                #     # convert weight from nhwc to nchw
+                #     Swichter().nhwc2nchw_one_slice_add_head(
+                #         'yolo/datas/multiobjects/float32s_nhwc/' + j + '.bin',
+                #         'yolo/datas/multiobjects/float32s_nchw_with_head/' + j,
+                #         'yolo/datas/multiobjects/float32s_nchw/' + j + '.tmp',
+                #         dims_of_matrix[0],
+                #         dims_of_matrix[1],
+                #         dims_of_matrix[2],
+                #         dims_of_matrix[3]
+                #     )
+                # else:
+                #     Swichter().copy_add_head(
+                #         'yolo/datas/multiobjects/float32s_nhwc/' + j + '.bin',
+                #         'yolo/datas/multiobjects/float32s_nchw_with_head/' + j,
+                #         'yolo/datas/multiobjects/float32s_nchw/' + j + '.tmp'
+                #     )
+            else:
+                vars_add.persistable = 0
+
+
+mdl_path = "datas/sourcemodels/cls231_0802/mobileNetModel.json"
+base_dir = "/Users/xiebaiyuan/PaddleProject/paddle-mobile/tools/python/modeltools/mobilenet/"
+converter = Converter(base_dir, mdl_path)
+converter.convert()

python/tools/mdl2fluid/swicher.py → tools/python/modeltools/mobilenet/swicher.py

@@ -58,7 +58,7 @@ class Swichter:
         to_file = open(to_file_name, "wb")
 
         tmp = tmp_file.read()
-        head = self.read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/yolo/conv1_biases')
+        head = self.read_head('yolo/datas/yolo/conv1_biases')
         to_file.write(head)
         to_file.write(tmp)
         tmp_file.close()
@@ -77,7 +77,7 @@ class Swichter:
         to_file = open(to_file_name, "wb")
         # tmp_file = open(tmp_file_name, "wb")
 
-        head = self.read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/yolo/conv1_biases')
+        head = self.read_head('yolo/datas/yolo/conv1_biases')
         to_file.write(head)
         to_file.write(from_file.read())
         from_file.close()
@@ -96,7 +96,7 @@ class Swichter:
         to_file = open(to_file_name, "wb")
         # tmp_file = open(tmp_file_name, "wb")
 
-        head = self.read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/yolo/conv1_biases')
+        head = self.read_head('yolo/datas/yolo/conv1_biases')
         to_file.write(head)
         to_file.write(read)
         from_file.close()
@@ -104,12 +104,12 @@ class Swichter:
         pass
 
 # Swichter().nhwc2nchw_one_slice_add_head(
-#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nhwc/conv1_0.bin',
-#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nchw_with_head/conv1_0',
-#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nchw/.tmp',
+#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/multiobjects/float32s_nhwc/conv1_0.bin',
+#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/multiobjects/float32s_nchw_with_head/conv1_0',
+#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/multiobjects/float32s_nchw/.tmp',
 #     32,
 #     3, 3, 3)
 
-# Swichter().read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/yolo/conv1_biases')
+# Swichter().read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/yolo/conv1_biases')
 
 # Swichter().copy_add_head('datas/model.0.0.weight', 'datas/conv1_0', '')

python/tools/mdl2fluid/loader.py → tools/python/modeltools/tools/loader.py

-import datetime
 import json
-import os
-
-import google.protobuf as pbg
-import framework_pb2 as framework_pb2
 
 
 def loadmdl(json_path):

python/tools/mdl2fluid/model_reader.py → tools/python/modeltools/tools/model_reader.py

 import os
 
-import framework_pb2 as framework_pb2
+from core import framework_pb2 as framework_pb2
 
 
 def read_model(model_path):
@@ -16,7 +16,7 @@ def read_model(model_path):
             # print desc.blocks
 
     except IOError:
-        print ": File not found.  Creating a new file."
+        print ": File not found."
 
 
 def get_file_size(file_path):
@@ -26,5 +26,5 @@ def get_file_size(file_path):
     return round(fsize, 2)
 
 
-path = "newyolo/__model__"
+path = '/Users/xiebaiyuan/PaddleProject/paddle-mobile/tools/python/modeltools/mobilenet/datas/sourcemodels/mobilenet_example/mobilenet/__model__'
 read_model(path)

python/tools/mdl2fluid/mdl2fluid.py → tools/python/modeltools/yolo/mdl2fluid.py

 import json
-import os
 
-import framework_pb2 as framework_pb2
-import op_types as types
-from swicher import Swichter
+from core import framework_pb2 as framework_pb2, op_types as types
+from yolo.swicher import Swichter
 import shutil
 
 
@@ -40,10 +38,10 @@ class Converter:
         print self.program_desc.blocks
         print 'convert end.....'
         desc_serialize_to_string = self.program_desc.SerializeToString()
-        shutil.rmtree('newyolo/')
-        shutil.copytree('multiobjects/float32s_nchw_with_head', 'newyolo/')
+        shutil.rmtree('yolo/datas/newyolo/')
+        shutil.copytree('yolo/datas/multiobjects/float32s_nchw_with_head/', 'yolo/datas/newyolo/')
 
-        f = open("newyolo/__model__", "wb")
+        f = open("yolo/datas/newyolo/__model__", "wb")
         f.write(desc_serialize_to_string)
         f.close()
 
@@ -312,9 +310,9 @@ class Converter:
                 if dims_size == 4:
                     # convert weight from nhwc to nchw
                     Swichter().nhwc2nchw_one_slice_add_head(
-                        '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nhwc/' + j + '.bin',
-                        '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nchw_with_head/' + j,
-                        '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nchw/' + j + '.tmp',
+                        'yolo/datas/multiobjects/float32s_nhwc/' + j + '.bin',
+                        'yolo/datas/multiobjects/float32s_nchw_with_head/' + j,
+                        'yolo/datas/multiobjects/float32s_nchw/' + j + '.tmp',
                         dims_of_matrix[0],
                         dims_of_matrix[1],
                         dims_of_matrix[2],
@@ -322,14 +320,14 @@ class Converter:
                     )
                 else:
                     Swichter().copy_add_head(
-                        '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nhwc/' + j + '.bin',
-                        '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nchw_with_head/' + j,
-                        '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/float32s_nchw/' + j + '.tmp'
+                        'yolo/datas/multiobjects/float32s_nhwc/' + j + '.bin',
+                        'yolo/datas/multiobjects/float32s_nchw_with_head/' + j,
+                        'yolo/datas/multiobjects/float32s_nchw/' + j + '.tmp'
                     )
             else:
                 vars_add.persistable = 0
 
 
-mdl_path = "/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/mdl2fluid/multiobjects/YOLO_Universal.json"
+mdl_path = "yolo/datas/multiobjects/YOLO_Universal.json"
 converter = Converter(mdl_path)
 converter.convert()

tools/python/modeltools/yolo/swicher.py

+from array import array
+
+
+class Swichter:
+    def __init__(self):
+        pass
+
+    def nhwc2nchw_one_slice(self, from_file_name, to_file_name, batch, channel, height, width):
+        from_file = open(from_file_name, "rb")
+        to_file = open(to_file_name, "wb")
+
+        float_array = array("f")
+        float_array.fromfile(from_file, width * height * batch * channel)
+        float_write_array = array("f")
+
+        for b in range(batch):
+            for c in range(channel):
+                for h in range(height):
+                    for w in range(width):
+                        float_value = float_array[b * channel * width * height
+                                                  + channel * (h * width + w) + c]
+
+                        float_write_array.append(float_value)
+
+        float_write_array.tofile(to_file)
+        from_file.close()
+        to_file.close()
+
+    def copy(self, from_file_name, to_file_name):
+        from_file = open(from_file_name, "rb")
+        to_file = open(to_file_name, "wb")
+
+        to_file.write(from_file.read())
+        from_file.close()
+        to_file.close()
+
+    def nhwc2nchw_one_slice_add_head(self, from_file_name, to_file_name, tmp_file_name, batch, channel, height, width):
+        from_file = open(from_file_name, "rb")
+        tmp_file = open(tmp_file_name, "wb+")
+        float_array = array("f")
+        float_array.fromfile(from_file, width * height * batch * channel)
+        float_write_array = array("f")
+
+        for b in range(batch):
+            for c in range(channel):
+                for h in range(height):
+                    for w in range(width):
+                        float_value = float_array[b * channel * width * height
+                                                  + channel * (h * width + w) + c]
+
+                        float_write_array.append(float_value)
+
+        float_write_array.tofile(tmp_file)
+        tmp_file.close()
+        from_file.close()
+
+        tmp_file = open(tmp_file_name, "rb")
+        to_file = open(to_file_name, "wb")
+
+        tmp = tmp_file.read()
+        head = self.read_head('yolo/datas/yolo/conv1_biases')
+        to_file.write(head)
+        to_file.write(tmp)
+        tmp_file.close()
+        to_file.close()
+
+    def read_head(self, head_file):
+        from_file = open(head_file, "rb")
+        read = from_file.read(24)
+        # print read
+        from_file.close()
+        # print read
+        return read
+
+    def copy_add_head(self, from_file_name, to_file_name, tmp_file_name):
+        from_file = open(from_file_name, "rb")
+        to_file = open(to_file_name, "wb")
+        # tmp_file = open(tmp_file_name, "wb")
+
+        head = self.read_head('yolo/datas/yolo/conv1_biases')
+        to_file.write(head)
+        to_file.write(from_file.read())
+        from_file.close()
+        to_file.close()
+        pass
+
+    def copy_padding_add_head(self, from_file_name, to_file_name, tmp_file_name, padding):
+        print'padding  = %d' % padding
+        from_file = open(from_file_name, "rb")
+        # print len(from_file.read())
+        from_file.seek(padding, 0)
+
+        read = from_file.read()
+        print len(read)
+
+        to_file = open(to_file_name, "wb")
+        # tmp_file = open(tmp_file_name, "wb")
+
+        head = self.read_head('yolo/datas/yolo/conv1_biases')
+        to_file.write(head)
+        to_file.write(read)
+        from_file.close()
+        to_file.close()
+        pass
+
+# Swichter().nhwc2nchw_one_slice_add_head(
+#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/multiobjects/float32s_nhwc/conv1_0.bin',
+#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/multiobjects/float32s_nchw_with_head/conv1_0',
+#     '/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/multiobjects/float32s_nchw/.tmp',
+#     32,
+#     3, 3, 3)
+
+# Swichter().read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/yolo/conv1_biases')
+
+# Swichter().copy_add_head('datas/model.0.0.weight', 'datas/conv1_0', '')