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Paddle-Lite
提交 6aec2006 编写于 作者: R Ray Liu 提交者： GitHub
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Merge pull request #1142 from xiebaiyuan/develop_python_develop 

add mobile net convert tools && fix bug in deepwises2p0 close #1141
上级 37314e68 ab1a2638
隐藏空白更改
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Showing with 248 addition and 66 deletion
src/operators/math/depthwise_conv_3x3.cpp
浏览文件 @ 6aec2006
......@@ -1667,7 +1667,7 @@ void DepthwiseConvAddBNRelu3x3s2p1v2(const Tensor *input, const Tensor *filter,
const int w_times = (out_w - 2) / 3;
float32x4_t zero = vdupq_n_f32(0.0);
for (int b = batch_size; b > 0; --b) {
#pragma omp parallel for
#pragma omp parallel for
for (int j = 0; j < c; j++) {
const float *input_row_ptr;
float *output_row_ptr;
......@@ -1901,7 +1901,9 @@ void DepthwiseConv3x3s2p0(const Tensor *input, const Tensor *filter,
for (int c = 0; c < input_channel; c++) {
const float *filter_data = filter->data<float>() + c * 9;
const float *input_data = input->data<float>() + c * inhxw;
const float *bias_data = bias.data<float>() + c;
if (if_bias) {
const float *bias_data = bias.data<float>() + c;
}
float *output_data = output->data<float>() + c * outhxw;
float w00 = filter_data[0];
float w01 = filter_data[1];
......@@ -1912,9 +1914,9 @@ void DepthwiseConv3x3s2p0(const Tensor *input, const Tensor *filter,
float w20 = filter_data[6];
float w21 = filter_data[7];
float w22 = filter_data[8];
float32x4_t biasv = vld1q_dup_f32(bias_data);
if (if_bias) {
float32x4_t biasv = vld1q_dup_f32(bias_data);
}
for (int i = 0; i < output_height; i += 1) {
for (int m = 0; m < output_width - 2; m += 3) {
float *output_ptr = output_data + i * output_width + m;
......@@ -1949,8 +1951,9 @@ void DepthwiseConv3x3s2p0(const Tensor *input, const Tensor *filter,
out0 = vmlaq_n_f32(out0, in4, w20);
out0 = vmlaq_n_f32(out0, tmp4, w21);
out0 = vmlaq_n_f32(out0, tmp5, w22);
out0 = vaddq_f32(out0, biasv);
if (if_bias) {
out0 = vaddq_f32(out0, biasv);
}
vst1q_lane_f32(output_ptr, out0, 0);
vst1q_lane_f32(output_ptr + 1, out0, 1);
vst1q_lane_f32(output_ptr + 2, out0, 2);
......@@ -1960,16 +1963,18 @@ void DepthwiseConv3x3s2p0(const Tensor *input, const Tensor *filter,
}
for (int j = m; j < output_width; j++) {
output_data[i * output_width + j] =
input_data[(2 * i - 1) * input_width + 2 * j - 1] * w00 +
input_data[(2 * i - 1) * input_width + 2 * j] * w01 +
input_data[(2 * i - 1) * input_width + 2 * j + 1] * w02 +
input_data[(2 * i) * input_width + 2 * j - 1] * w10 +
input_data[(2 * i) * input_width + 2 * j] * w11 +
input_data[(2 * i) * input_width + 2 * j + 1] * w12 +
input_data[(2 * i + 1) * input_width + 2 * j - 1] * w20 +
input_data[(2 * i + 1) * input_width + 2 * j] * w21 +
input_data[(2 * i + 1) * input_width + 2 * j + 1] * w22;
output_data[i * output_width + j] += *bias_data;
input_data[(2 * i) * input_width + 2 * j] * w00 +
input_data[(2 * i) * input_width + 2 * j + 1] * w01 +
input_data[(2 * i) * input_width + 2 * j + 2] * w02 +
input_data[(2 * i + 1) * input_width + 2 * j] * w10 +
input_data[(2 * i + 1) * input_width + 2 * j + 1] * w11 +
input_data[(2 * i + 1) * input_width + 2 * j + 2] * w12 +
input_data[(2 * i + 2) * input_width + 2 * j] * w20 +
input_data[(2 * i + 2) * input_width + 2 * j + 1] * w21 +
input_data[(2 * i + 2) * input_width + 2 * j + 2] * w22;
if (if_bias) {
output_data[i * output_width + j] += *bias_data;
}
}
}
}
......
tools/op.cmake
浏览文件 @ 6aec2006
......@@ -33,6 +33,7 @@ if (CON GREATER -1)
set(POOL_OP ON)
set(RESHAPE_OP ON)
set(FUSION_CONVADDBNRELU_OP ON)
set(FUSION_CONVADDRELU_OP ON)
set(FUSION_CONVADD_OP ON)
set(FOUND_MATCH ON)
......
tools/python/imagetools/img2nchw.py
浏览文件 @ 6aec2006
......@@ -45,13 +45,13 @@ def combine_bgrs_nchw(bgrs, means_b_g_r, scale, channel_type=ChannelType.BGR):
print '------------------'
print bgrs_float_array[0]
print bgrs_float_array[416 * 416 * 2 + 416 * 2 + 2]
print bgrs_float_array[224 * 224 * 2 + 224 * 2 + 2]
# for i in range(0, 9):
# print'bs %d' % i
# print bs[i] / 255.
print bs[416 * 2 + 2] / 255.
print bs[224 * 2 + 2] / 255.
print '--------------combine_bgrs_nchw-----------------end'
return bgrs_float_array
......@@ -64,6 +64,6 @@ def combine_bgrs_nchw(bgrs, means_b_g_r, scale, channel_type=ChannelType.BGR):
# cv2.waitKey(0)
bgrs = tools.resize_take_rgbs('datas/newyolo.jpg', (416, 416, 3))
bgrs = tools.resize_take_rgbs('datas/jpgs/0000_0.9834-148196_82452-0ad4b83ec6bc0f9c5f28101539267054.jpg_p0_0.126571263346.jpg', (224, 224, 3))
array = combine_bgrs_nchw(bgrs, (0, 0, 0), 1. / 255, ChannelType.RGB)
tools.save_to_file('datas/desktop_1_3_416_416_nchw_float', array)
tools.save_to_file('datas/desktop_1_3_224_224_nchw_float', array)
tools/python/imagetools/numpy2binary.py
浏览文件 @ 6aec2006
......@@ -15,11 +15,11 @@ from array import array
# image.resize(shape_h_w)
data = np.fromfile('datas/img.res')
data = np.fromfile('/Users/xiebaiyuan/PaddleProject/paddle-mobile/tools/python/imagetools/datas/jpgs2/0000_0.9834-148196_82452-0ad4b83ec6bc0f9c5f28101539267054.jpg_p0_0.126571263346.jpg.input.npfile','f')
print data.size
print data[0]
print data
data.reshape(1, 3, 416, 416)
data.reshape(1, 3, 224, 224)
out_array = array('f')
print'--------------------'
print data.size
......@@ -27,12 +27,12 @@ print data[0]
print '如果是nhwc --------'
# rgb rgb rgb rgb rgb
print data[416 * 3 * 2 + 3 * 2 + 2]
print data[224 * 3 * 2 + 3 * 2 + 2]
# print data[2]
print '如果是nchw --------'
# rgb rgb rgb rgb rgb
print data[416 * 416 * 2 + 416 * 2 + 2]
print data[224 * 224 * 2 + 224 * 2 + 2]
# print data[2]
# 明明是nchw
......@@ -42,6 +42,8 @@ for i in range(0, data.size):
print len(out_array)
print out_array[416 * 416 * 2 + 416 * 2 + 2]
print out_array[224 * 224 * 2 + 224 * 2 + 2]
# print out_array
tools.save_to_file('datas/in_put_1_3_416_416_2', out_array)
tools.save_to_file('datas/in_put_1_3_224_224_nchw', out_array)
tools/python/modeltools/core/op_types.py
浏览文件 @ 6aec2006
......@@ -77,6 +77,14 @@ fusion_conv_add_attrs_dict = {
'strides': 'stride',
'groups': 'group'
}
# fluid attr key --- mdl params key
pool2d_attrs_dict = {
'global_pooling': 'global_pooling',
'pooling_type': 'type'
}
# fluid attr key --- mdl params key
fluid_attrs_type_dict = {
'paddings': 0,
......
tools/python/modeltools/mobilenet/converter_mobilenet.py
浏览文件 @ 6aec2006
# coding=utf-8
import json
import os
......@@ -12,13 +13,25 @@ def load_mdl(mdl_json_path):
return json.load(f)
def create_if_not_exit(target_dir):
if os.path.exists(target_dir):
shutil.rmtree(target_dir)
os.makedirs(target_dir, 0777)
class Converter:
'convert mdlmodel to fluidmodel'
def __init__(self, base_dir, mdl_json_path):
print 'base_dir: ' + base_dir
self.mdl_json_path = base_dir + mdl_json_path
self.base_dir = base_dir
print mdl_json_path
self.source_weights_dir = self.base_dir + 'datas/sourcemodels/source_weights/'
self.target_weight_dir = self.base_dir + 'datas/target/target_weights/'
create_if_not_exit(self.target_weight_dir)
self.mdl_json = load_mdl(self.mdl_json_path)
self.program_desc = framework_pb2.ProgramDesc()
self.weight_list_ = []
......@@ -41,16 +54,18 @@ class Converter:
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/')
outputmodel_dir = self.base_dir + 'datas/target/mobilenet_classfication/'
if os.path.exists(outputmodel_dir):
shutil.rmtree(outputmodel_dir)
os.makedirs(outputmodel_dir, 0777)
f = open(outputmodel_ + "__model__", "wb")
if os.path.exists(outputmodel_dir):
shutil.rmtree(outputmodel_dir)
# create_if_not_exit(outputmodel_dir)
shutil.copytree(self.target_weight_dir, outputmodel_dir)
f = open(outputmodel_dir + "__model__", "wb")
f.write(desc_serialize_to_string)
f.close()
......@@ -63,26 +78,30 @@ class Converter:
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 layer['type'] == 'SoftmaxLayer':
pass
else:
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 'weight' in layer:
self.package_ops_weight2inputs(desc_ops_add, layer)
if 'output' in layer:
self.package_ops_outputs(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)
if 'input' in layer:
self.package_ops_inputs(desc_ops_add, layer)
self.package_ops_attrs(desc_ops_add, layer)
self.package_ops_attrs(desc_ops_add, layer)
self.add_op_fetch(block_desc)
......@@ -105,7 +124,8 @@ class Converter:
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')
# todo pick last layer --> op output
inputs_add.arguments.append('fc7')
desc_ops_add.type = 'fetch'
outputs_add = desc_ops_add.outputs.add()
outputs_add.parameter = 'Out'
......@@ -129,6 +149,128 @@ class Converter:
# boolean
attrs_add.type = 6
attrs_add.b = 0
elif desc_ops_add.type == types.op_fluid_pooling:
Converter.pack_pooling_attr(desc_ops_add, layer)
pass
elif desc_ops_add.type == types.op_fluid_softmax:
pass
@staticmethod
def pack_pooling_attr(desc_ops_add, layer):
print layer
l_params = layer['param']
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 = 'paddings'
# ints
attrs_add.type = 3
attrs_add.ints.append(0)
attrs_add.ints.append(0)
attrs_add = desc_ops_add.attrs.add()
attrs_add.name = 'strides'
# 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 = 'global_pooling'
# boolean
attrs_add.type = 6
attrs_add.b = (l_params[types.pool2d_attrs_dict.get('global_pooling')])
attrs_add = desc_ops_add.attrs.add()
attrs_add.name = 'pooling_type'
# 2-->STRING
attrs_add.type = 2
# 注意这里 avg but mdl is ave
attrs_add.s = l_params[types.pool2d_attrs_dict.get('pooling_type')]
attrs_add = desc_ops_add.attrs.add()
attrs_add.name = 'ceil_mode'
# boolean
attrs_add.type = 6
attrs_add.b = 1
attrs_add = desc_ops_add.attrs.add()
attrs_add.name = 'ksize'
# ints
attrs_add.type = 3
attrs_add.ints.append(7)
attrs_add.ints.append(7)
# type: "pool2d"
# attrs
# {
# name: "use_mkldnn"
# type: BOOLEAN
# b: false
# }
# attrs
# {
# name: "ceil_mode"
# type: BOOLEAN
# b: true
# }
# attrs
# {
# name: "use_cudnn"
# type: BOOLEAN
# b: true
# }
# attrs
# {
# name: "paddings"
# type: INTS
# ints: 0
# ints: 0
# }
# attrs
# {
# name: "strides"
# type: INTS
# ints: 1
# ints: 1
# }
# attrs
# {
# name: "global_pooling"
# type: BOOLEAN
# b: false
# }
# attrs
# {
# name: "data_format"
# type: STRING
# s: "AnyLayout"
# }
# attrs
# {
# name: "ksize"
# type: INTS
# ints: 7
# ints: 7
# }
# attrs
# {
# name: "pooling_type"
# type: STRING
# s: "avg"
# }
# is_target: false
@staticmethod
def pack_fusion_conv_add_attr(desc_ops_add, layer):
......@@ -181,6 +323,13 @@ class Converter:
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 = 'paddings'
# # ints
# attrs_add.type = 3
# attrs_add.ints.append(0)
# attrs_add.ints.append(0)
attrs_add = desc_ops_add.attrs.add()
attrs_add.name = 'strides'
# ints
......@@ -188,6 +337,13 @@ class Converter:
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 = 'strides'
# # ints
# attrs_add.type = 3
# attrs_add.ints.append(6)
# attrs_add.ints.append(6)
attrs_add = desc_ops_add.attrs.add()
attrs_add.name = 'groups'
# int
......@@ -232,8 +388,8 @@ class Converter:
# 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
# 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)
......@@ -305,7 +461,7 @@ class Converter:
# issues in mdl model filter swich n and c
if j in self.deepwise_weight_list_ and len(dims_of_matrix) == 4:
print j
print "deep wise issue fit: " + j
tensor.dims.append(dims_of_matrix[1])
tensor.dims.append(dims_of_matrix[0])
tensor.dims.append(dims_of_matrix[2])
......@@ -320,6 +476,12 @@ class Converter:
vars_add.persistable = 1
dims_size = len(dims_of_matrix)
# print dims_size
# print 'weight name : ' + j
Swichter().copy_add_head(
self.source_weights_dir + j + '.bin',
self.target_weight_dir + j
)
# if dims_size == 4:
# # convert weight from nhwc to nchw
# Swichter().nhwc2nchw_one_slice_add_head(
......@@ -341,7 +503,7 @@ class Converter:
vars_add.persistable = 0
mdl_path = "datas/sourcemodels/cls231_0802/mobileNetModel.json"
mdl_path = "datas/sourcemodels/source_profile/mobileNetModel.json"
base_dir = "/Users/xiebaiyuan/PaddleProject/paddle-mobile/tools/python/modeltools/mobilenet/"
converter = Converter(base_dir, mdl_path)
converter.convert()
tools/python/modeltools/mobilenet/swicher.py
浏览文件 @ 6aec2006
import os
import shutil
from array import array
......@@ -58,7 +60,7 @@ class Swichter:
to_file = open(to_file_name, "wb")
tmp = tmp_file.read()
head = self.read_head('yolo/datas/yolo/conv1_biases')
head = self.read_head('yolo/datas/yolo/head')
to_file.write(head)
to_file.write(tmp)
tmp_file.close()
......@@ -72,12 +74,14 @@ class Swichter:
# print read
return read
def copy_add_head(self, from_file_name, to_file_name, tmp_file_name):
def copy_add_head(self, from_file_name, to_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')
head = self.read_head(
'/Users/xiebaiyuan/PaddleProject/paddle-mobile/tools/python/modeltools/mobilenet/datas/sourcemodels/head/head')
to_file.write(head)
to_file.write(from_file.read())
from_file.close()
......@@ -96,7 +100,7 @@ class Swichter:
to_file = open(to_file_name, "wb")
# tmp_file = open(tmp_file_name, "wb")
head = self.read_head('yolo/datas/yolo/conv1_biases')
head = self.read_head('yolo/datas/yolo/head')
to_file.write(head)
to_file.write(read)
from_file.close()
......@@ -110,6 +114,6 @@ class Swichter:
# 32,
# 3, 3, 3)
# Swichter().read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/yolo/conv1_biases')
# Swichter().read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/yolo/head')
# Swichter().copy_add_head('datas/model.0.0.weight', 'datas/conv1_0', '')
tools/python/modeltools/yolo/swicher.py
浏览文件 @ 6aec2006
......@@ -58,7 +58,7 @@ class Swichter:
to_file = open(to_file_name, "wb")
tmp = tmp_file.read()
head = self.read_head('yolo/datas/yolo/conv1_biases')
head = self.read_head('yolo/datas/yolo/head')
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('yolo/datas/yolo/conv1_biases')
head = self.read_head('yolo/datas/yolo/head')
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('yolo/datas/yolo/conv1_biases')
head = self.read_head('yolo/datas/yolo/head')
to_file.write(head)
to_file.write(read)
from_file.close()
......@@ -110,6 +110,6 @@ class Swichter:
# 32,
# 3, 3, 3)
# Swichter().read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/yolo/conv1_biases')
# Swichter().read_head('/Users/xiebaiyuan/PaddleProject/paddle-mobile/python/tools/modeltools/yolo/head')
# Swichter().copy_add_head('datas/model.0.0.weight', 'datas/conv1_0', '')
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