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提交 c8d90837 编写于 作者: J jiazhenwei
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campate python3 with six, basic usage command convert run passed, maybe need more test

上级 3c1fcc20
隐藏空白更改
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Showing with 209 addition and 165 deletion
.gitignore
浏览文件 @ c8d90837
......@@ -19,3 +19,5 @@ builds/
mace/examples/android/macelibrary/src/main/cpp/mace/
\.project/
*swp
*~
mace/python/tools/binary_codegen.py
浏览文件 @ c8d90837
......@@ -20,6 +20,8 @@ import struct
import jinja2
import numpy as np
import six
# python mace/python/tools/binary_codegen.py \
# --binary_dirs=${BIN_FILE} \
......@@ -39,11 +41,11 @@ def generate_cpp_source(binary_dirs, binary_file_name, variable_name):
with open(binary_path, "rb") as f:
binary_array = np.fromfile(f, dtype=np.uint8)
print "Generate binary from", binary_path
six.print_("Generate binary from", binary_path)
idx = 0
size, = struct.unpack("Q", binary_array[idx:idx + 8])
idx += 8
for _ in xrange(size):
for _ in six.moves.range(size):
key_size, = struct.unpack("i", binary_array[idx:idx + 4])
idx += 4
key, = struct.unpack(
......
mace/python/tools/convert_util.py
浏览文件 @ c8d90837
......@@ -21,7 +21,7 @@ def mace_check(condition, msg):
def roundup_div4(value):
return int((value + 3) / 4)
return int((value + 3) // 4)
class OpenCLBufferType(enum.Enum):
......
mace/python/tools/converter.py
浏览文件 @ c8d90837
......@@ -18,6 +18,8 @@ import hashlib
import os.path
import copy
import six
from mace.proto import mace_pb2
from mace.python.tools import memory_optimizer
from mace.python.tools import model_saver
......@@ -25,7 +27,6 @@ from mace.python.tools.converter_tool import base_converter as cvt
from mace.python.tools.converter_tool import transformer
from mace.python.tools.convert_util import mace_check
# ./bazel-bin/mace/python/tools/tf_converter --model_file quantized_test.pb \
# --output quantized_test_dsp.pb \
# --runtime dsp \
......@@ -70,34 +71,39 @@ def parse_float_array_from_str(ints_str):
def main(unused_args):
if not os.path.isfile(FLAGS.model_file):
print("Input graph file '" + FLAGS.model_file + "' does not exist!")
six.print_("Input graph file '" +
FLAGS.model_file +
"' does not exist!", file=sys.stderr)
sys.exit(-1)
model_checksum = file_checksum(FLAGS.model_file)
if FLAGS.model_checksum != "" and FLAGS.model_checksum != model_checksum:
print("Model checksum mismatch: %s != %s" % (model_checksum,
FLAGS.model_checksum))
six.print_("Model checksum mismatch: %s != %s" %
(model_checksum, FLAGS.model_checksum), file=sys.stderr)
sys.exit(-1)
weight_checksum = None
if FLAGS.platform == 'caffe':
if not os.path.isfile(FLAGS.weight_file):
print("Input weight file '" + FLAGS.weight_file +
"' does not exist!")
six.print_("Input weight file '" + FLAGS.weight_file +
"' does not exist!", file=sys.stderr)
sys.exit(-1)
weight_checksum = file_checksum(FLAGS.weight_file)
if FLAGS.weight_checksum != "" and \
FLAGS.weight_checksum != weight_checksum:
print("Weight checksum mismatch: %s != %s" %
(weight_checksum, FLAGS.weight_checksum))
six.print_("Weight checksum mismatch: %s != %s" %
(weight_checksum, FLAGS.weight_checksum),
file=sys.stderr)
sys.exit(-1)
if FLAGS.platform not in ['tensorflow', 'caffe']:
print ("platform %s is not supported." % FLAGS.platform)
six.print_("platform %s is not supported." % FLAGS.platform,
file=sys.stderr)
sys.exit(-1)
if FLAGS.runtime not in ['cpu', 'gpu', 'dsp', 'cpu+gpu']:
print ("runtime %s is not supported." % FLAGS.runtime)
six.print_("runtime %s is not supported." % FLAGS.runtime,
file=sys.stderr)
sys.exit(-1)
option = cvt.ConverterOption()
......@@ -117,7 +123,7 @@ def main(unused_args):
input_node_ranges = []
if len(input_node_names) != len(input_node_shapes):
raise Exception('input node count and shape count do not match.')
for i in xrange(len(input_node_names)):
for i in six.moves.range(len(input_node_names)):
input_node = cvt.NodeInfo()
input_node.name = input_node_names[i]
input_node.shape = parse_int_array_from_str(input_node_shapes[i])
......@@ -126,7 +132,7 @@ def main(unused_args):
option.add_input_node(input_node)
output_node_names = FLAGS.output_node.split(',')
for i in xrange(len(output_node_names)):
for i in six.moves.range(len(output_node_names)):
output_node = cvt.NodeInfo()
output_node.name = output_node_names[i]
option.add_output_node(output_node)
......@@ -152,7 +158,8 @@ def main(unused_args):
FLAGS.model_file,
FLAGS.weight_file)
else:
print("Mace do not support platorm %s yet." & FLAGS.platform)
six.print_("Mace do not support platorm %s yet." % FLAGS.platform,
file=sys.stderr)
exit(1)
output_graph_def = converter.run()
......@@ -166,9 +173,9 @@ def main(unused_args):
mace_gpu_transformer = transformer.Transformer(
option, output_graph_def)
output_graph_def = mace_gpu_transformer.run()
print "start optimize gpu memory."
six.print_("start optimize gpu memory.")
memory_optimizer.optimize_gpu_memory(output_graph_def)
print "GPU memory optimization done."
six.print_("GPU memory optimization done.")
option.device = cvt.DeviceType.CPU.value
option.data_type = parse_data_type(
......@@ -177,11 +184,11 @@ def main(unused_args):
mace_cpu_transformer = transformer.Transformer(
option, cpu_graph_def)
cpu_graph_def = mace_cpu_transformer.run()
print "start optimize cpu memory."
print("start optimize cpu memory.")
memory_optimizer.optimize_cpu_memory(cpu_graph_def)
print "CPU memory optimization done."
print("CPU memory optimization done.")
print "Merge cpu and gpu ops together"
print("Merge cpu and gpu ops together")
output_graph_def.op.extend(cpu_graph_def.op)
output_graph_def.mem_arena.mem_block.extend(
cpu_graph_def.mem_arena.mem_block)
......@@ -192,7 +199,7 @@ def main(unused_args):
for arg in cpu_graph_def.arg:
if arg.name not in output_graph_arg_names:
output_graph_def.arg.extend(arg)
print "Merge done"
print("Merge done")
else:
option.device = device_type_map[FLAGS.runtime]
option.data_type = parse_data_type(
......@@ -201,7 +208,7 @@ def main(unused_args):
option, output_graph_def)
output_graph_def = mace_transformer.run()
print "start optimize memory."
print("start optimize memory.")
if FLAGS.runtime == 'gpu':
memory_optimizer.optimize_gpu_memory(output_graph_def)
elif FLAGS.runtime == 'cpu':
......@@ -209,7 +216,7 @@ def main(unused_args):
else:
mace_check(False, "runtime only support [gpu|cpu|dsp]")
print "Memory optimization done."
print("Memory optimization done.")
model_saver.save_model(
output_graph_def, model_checksum, weight_checksum,
......@@ -238,7 +245,7 @@ def parse_args():
type=str,
default="",
help="TensorFlow \'GraphDef\' file to load, "
"Caffe prototxt file to load.")
"Caffe prototxt file to load.")
parser.add_argument(
"--weight_file", type=str, default="", help="Caffe data file to load.")
parser.add_argument(
......@@ -302,7 +309,7 @@ def parse_args():
type=str,
default="file",
help="[file|code] build models to code" +
"or `Protobuf` file.")
"or `Protobuf` file.")
parser.add_argument(
"--data_type",
type=str,
......
mace/python/tools/converter_tool/caffe_converter.py
浏览文件 @ c8d90837
......@@ -14,7 +14,9 @@
import math
import numpy as np
import six
import google.protobuf.text_format
from mace.proto import mace_pb2
......@@ -46,6 +48,7 @@ class CaffeOperator(object):
Layer records caffe layer proto, while blobs records the weight data in
format of numpy ndarray.
"""
def __init__(self):
self._layer = None
self._blobs = None
......@@ -92,6 +95,7 @@ class CaffeNet(object):
"""CaffeNet contains caffe operations. Output of each layer has unique
name as we replace duplicated output name with unique one, while keep
mace input/output name which user specifies unchanged."""
def __init__(self):
self._ops = {}
self._consumers = {}
......@@ -119,7 +123,7 @@ class CaffeNet(object):
layer.bottom[:] = [self._alias_op_output_name.get(layer_input,
layer_input) for
layer_input in layer.bottom][:]
for i in xrange(len(layer.top)):
for i in six.moves.range(len(layer.top)):
old_name = layer.top[i]
if layer.type == 'Input':
new_name = old_name
......@@ -218,7 +222,7 @@ class CaffeConverter(base_converter.ConverterInterface):
@staticmethod
def replace_input_name(ops, src_name, dst_name):
for op in ops:
for i in xrange(len(op.input)):
for i in six.moves.range(len(op.input)):
if op.input[i] == src_name:
op.input[i] = dst_name
......@@ -235,7 +239,7 @@ class CaffeConverter(base_converter.ConverterInterface):
ops.reverse()
visited = set()
for op in ops:
for i in xrange(len(op.output)):
for i in six.moves.range(len(op.output)):
original_output_name = op.output[i].split('#')[0]
if original_output_name not in visited:
self.replace_input_name(
......@@ -267,7 +271,7 @@ class CaffeConverter(base_converter.ConverterInterface):
if len(layer.exclude):
phase = phase_map[layer.exclude[0].phase]
if phase != 'test' or layer.type == 'Dropout':
print ("Remove layer %s (%s)" % (layer.name, layer.type))
print("Remove layer %s (%s)" % (layer.name, layer.type))
layers.layer.remove(layer)
changed = True
break
......@@ -497,8 +501,8 @@ class CaffeConverter(base_converter.ConverterInterface):
beta_value = scale_op.blobs[1]
scale_value = (
(1.0 / np.vectorize(math.sqrt)(var_value + epsilon_value)) *
gamma_value).reshape(-1)
(1.0 / np.vectorize(math.sqrt)(var_value + epsilon_value)) *
gamma_value).reshape(-1)
offset_value = ((-mean_value * scale_value) + beta_value).reshape(-1)
input_names = [op.name + '_scale', op.name + '_offset']
......
mace/python/tools/converter_tool/shape_inference.py
浏览文件 @ c8d90837
......@@ -14,7 +14,9 @@
import math
import numpy as np
import six
from mace.python.tools.converter_tool.transformer import Transformer
from mace.python.tools.converter_tool.base_converter import DataFormat
......@@ -68,7 +70,7 @@ class ShapeInference(object):
"Op %s (%s) output count is different from "
"output shape count" % (
op.name, op.type))
for i in xrange(len(shapes)):
for i in six.moves.range(len(shapes)):
output_name = op.output[i]
output_shape = op.output_shape.add()
output_shape.dims.extend(shapes[i])
......@@ -174,8 +176,8 @@ class ShapeInference(object):
mace_check(False,
"Mace can only infer shape for"
" NCHW input and OIHW filter")
print ("deconv layer %s (%s) input:%s filter:%s output:%s" %
(op.name, op.type, input_shape, filter_shape, output_shape))
print("deconv layer %s (%s) input:%s filter:%s output:%s" %
(op.name, op.type, input_shape, filter_shape, output_shape))
self.add_output_shape(op, [output_shape])
......
mace/python/tools/converter_tool/tensorflow_converter.py
浏览文件 @ c8d90837
......@@ -15,6 +15,7 @@
import math
import numpy as np
import six
import tensorflow as tf
from enum import Enum
......
mace/python/tools/converter_tool/tf_dsp_converter.py
浏览文件 @ c8d90837
......@@ -18,6 +18,7 @@ from mace.python.tools.converter_tool import base_converter
from mace.python.tools import graph_util
from mace.python.tools.convert_util import mace_check
import six
import tensorflow as tf
from tensorflow.core.framework import tensor_shape_pb2
from operator import mul
......@@ -506,8 +507,8 @@ def reverse_batch_to_space_and_biasadd(net_def):
for follow_op in follow_ops:
new_follow_op = mace_pb2.OperatorDef()
new_follow_op.CopyFrom(follow_op)
for i in xrange(len(follow_op.input)):
for k in xrange(3):
for i in six.moves.range(len(follow_op.input)):
for k in six.moves.range(3):
if new_follow_op.input[i] == get_tensor_name_from_op( # noqa
biasadd_requantize_op.name, k):
new_follow_op.input[i] = get_tensor_name_from_op( # noqa
......@@ -560,7 +561,7 @@ def add_input_output_info(net_def, input_node, output_node, graph, dtype):
input_info.dims.extend(input_tensor.shape.as_list())
input_info.data_type = dtype
if dtype == mace_pb2.DT_UINT8:
for i in xrange(2):
for i in six.moves.range(2):
input_info = net_def.input_info.add()
input_info.dims.extend([1, 1, 1, 1])
input_info.data_type = mace_pb2.DT_FLOAT
......@@ -570,7 +571,7 @@ def add_input_output_info(net_def, input_node, output_node, graph, dtype):
output_info.dims.extend(output_tensor.shape.as_list())
output_info.data_type = dtype
if dtype == mace_pb2.DT_UINT8:
for i in xrange(2):
for i in six.moves.range(2):
output_info = net_def.output_info.add()
output_info.dims.extend([1, 1, 1, 1])
output_info.data_type = mace_pb2.DT_FLOAT
......
mace/python/tools/converter_tool/transformer.py
浏览文件 @ c8d90837
......@@ -14,9 +14,11 @@
import enum
import numpy as np
import re
import numpy as np
import six
from mace.proto import mace_pb2
from mace.python.tools.converter_tool import base_converter
from mace.python.tools.converter_tool.base_converter import ActivationType
......@@ -191,14 +193,14 @@ class Transformer(base_converter.ConverterInterface):
@staticmethod
def replace(obj_list, source, target):
for i in xrange(len(obj_list)):
for i in six.moves.range(len(obj_list)):
if obj_list[i] == source:
obj_list[i] = target
@staticmethod
def transpose_shape(shape, order):
transposed_shape = []
for i in xrange(len(order)):
for i in six.moves.range(len(order)):
transposed_shape.append(shape[order[i]])
shape[:] = transposed_shape[:]
......@@ -208,7 +210,7 @@ class Transformer(base_converter.ConverterInterface):
def get_tensor_shape(self, tensor):
producer = self._producer[tensor]
for i in xrange(len(producer.output)):
for i in six.moves.range(len(producer.output)):
if producer.output[i] == tensor:
return list(producer.output_shape[i].dims)
......@@ -247,7 +249,7 @@ class Transformer(base_converter.ConverterInterface):
"cannot remove op since len(op.output) "
"!= len(replace_op.output)")
for i in xrange(len(op.output)):
for i in six.moves.range(len(op.output)):
for consumer_op in self._consumers.get(op.output[i], []):
self.replace(consumer_op.input,
op.output[i],
......@@ -255,7 +257,7 @@ class Transformer(base_converter.ConverterInterface):
# if the op is output node, change replace_op output name to the op
# output name
for i in xrange(len(op.output)):
for i in six.moves.range(len(op.output)):
if op.output[i] in self._option.output_nodes:
for consumer in self._consumers.get(
replace_op.output[i], []):
......@@ -508,15 +510,17 @@ class Transformer(base_converter.ConverterInterface):
idx = 0
filter_format = self.filter_format()
if filter_format == FilterFormat.HWIO:
for hwi in xrange(filter.dims[0] * filter.dims[1]
* filter.dims[2]):
for o in xrange(filter.dims[3]):
for hwi in six.moves.range(filter.dims[0]
* filter.dims[1]
* filter.dims[2]):
for o in six.moves.range(filter.dims[3]):
filter.float_data[idx] *= scale.float_data[o]
idx += 1
elif filter_format == FilterFormat.OIHW:
for o in xrange(filter.dims[0]):
for hwi in xrange(filter.dims[1] * filter.dims[2]
* filter.dims[3]):
for o in six.moves.range(filter.dims[0]):
for hwi in six.moves.range(filter.dims[1]
* filter.dims[2]
* filter.dims[3]):
filter.float_data[idx] *= scale.float_data[o]
idx += 1
else:
......@@ -548,17 +552,18 @@ class Transformer(base_converter.ConverterInterface):
filter_format = self.filter_format()
if filter_format == FilterFormat.HWIO:
for hw in xrange(filter.dims[0] * filter.dims[1]):
for i in xrange(filter.dims[2]):
for o in xrange(filter.dims[3]):
for hw in six.moves.range(filter.dims[0]
* filter.dims[1]):
for i in six.moves.range(filter.dims[2]):
for o in six.moves.range(filter.dims[3]):
filter.float_data[idx] *= scale.float_data[
i * filter.dims[3] + o]
i * filter.dims[3] + o]
idx += 1
elif filter_format == FilterFormat.OIHW:
for o in xrange(filter.dims[0]):
for i in xrange(filter.dims[1]):
for hw in xrange(filter.dims[2]
* filter.dims[3]):
for o in six.moves.range(filter.dims[0]):
for i in six.moves.range(filter.dims[1]):
for hw in six.moves.range(filter.dims[2]
* filter.dims[3]):
filter.float_data[idx] *= scale.float_data[
i * filter.dims[0] + o]
idx += 1
......@@ -836,7 +841,7 @@ class Transformer(base_converter.ConverterInterface):
and len(self._consumers.get(conv_op.output[0], [])) == 1: # noqa
b2s_op = self._consumers.get(conv_op.output[0])[0]
if b2s_op.type == MaceOp.BatchToSpaceND.name:
print "Flatten atrous convolution"
six.print_("Flatten atrous convolution")
# Add args.
padding_arg_values = ConverterUtil.get_arg(
op,
......@@ -1167,7 +1172,7 @@ class Transformer(base_converter.ConverterInterface):
and len(self._consts[input].dims) == 2:
arg = ConverterUtil.get_arg(op, transpose_arg_names[i])
if arg is not None and arg.i == 1:
print 'convert matmul'
six.print_('convert matmul')
filter = self._consts[input]
filter_data = np.array(filter.float_data).reshape(
filter.dims)
......@@ -1494,7 +1499,7 @@ class Transformer(base_converter.ConverterInterface):
weight.dims[0] != op.output_shape[0].dims[1]:
is_fc = False
if is_fc:
print 'convert reshape and matmul to fc'
print('convert reshape and matmul to fc')
self.safe_remove_node(op, input_op,
remove_input_tensor=True)
for matmul_op in consumers:
......@@ -1515,7 +1520,7 @@ class Transformer(base_converter.ConverterInterface):
producer.type != MaceOp.Reshape.name and \
len(producer.output_shape[0].dims) == 2 and \
weight.dims[0] == producer.output_shape[0].dims[1]:
print 'convert matmul to fc'
six.print_('convert matmul to fc')
op.type = MaceOp.FullyConnected.name
weight_data = np.array(weight.float_data).reshape(
weight.dims)
......@@ -1840,7 +1845,7 @@ class Transformer(base_converter.ConverterInterface):
if not self._option.quantize:
return False
print ("Add default quantize info for ops like Pooling, Softmax")
print("Add default quantize info for ops like Pooling, Softmax")
for op in self._model.op:
if op.type in [MaceOp.Pooling.name,
MaceOp.Squeeze.name,
......@@ -1897,7 +1902,7 @@ class Transformer(base_converter.ConverterInterface):
self.add_quantize_info(op, minval, maxval)
self._quantize_activation_info[op.output[0]] = quantize_info
print ("Add default quantize info for input")
print("Add default quantize info for input")
for input_node in self._option.input_nodes.values():
if input_node.name not in self._quantize_activation_info:
print("Input range %s: %s" % (input_node.name,
......
mace/python/tools/memory_optimizer.py
浏览文件 @ c8d90837
......@@ -14,6 +14,9 @@
import sys
import operator
import six
from mace.proto import mace_pb2
from mace.python.tools.converter_tool import base_converter as cvt
......@@ -60,7 +63,7 @@ class MemoryOptimizer(object):
self.mem_ref_counter = {}
ocl_mem_type_arg = ConverterUtil.get_arg(
net_def, MaceKeyword.mace_opencl_mem_type)
self.cl_mem_type = ocl_mem_type_arg.i if ocl_mem_type_arg is not None\
self.cl_mem_type = ocl_mem_type_arg.i if ocl_mem_type_arg is not None \
else None
consumers = {}
......@@ -126,8 +129,8 @@ class MemoryOptimizer(object):
def get_total_optimized_mem_size(self):
optimized_mem_size = 0
for mem in self.mem_block:
print mem, MemoryTypeToStr(self.mem_block[mem].mem_type), \
self.mem_block[mem].block
print(mem, MemoryTypeToStr(self.mem_block[mem].mem_type),
self.mem_block[mem].block)
optimized_mem_size += self.mem_size(self.mem_block[mem])
return optimized_mem_size
......@@ -141,12 +144,14 @@ class MemoryOptimizer(object):
if not self.op_need_optimize_memory(op):
continue
if not op.output_shape:
print("WARNING: There is no output shape information to "
"do memory optimization. %s (%s)" % (op.name, op.type))
six.print_("WARNING: There is no output shape information to "
"do memory optimization. %s (%s)" %
(op.name, op.type), file=sys.stderr)
return
if len(op.output_shape) != len(op.output):
print('WARNING: the number of output shape is not equal to '
'the number of output.')
six.print_('WARNING: the number of output shape is '
'not equal to the number of output.',
file=sys.stderr)
return
for i in range(len(op.output)):
if self.is_memory_reuse_op(op):
......@@ -181,7 +186,7 @@ class MemoryOptimizer(object):
# minimize add_mem_size; if best_mem_add_size is 0,
# then minimize waste_mem_size
if (best_mem_add_size > 0 and
add_mem_size < best_mem_add_size) \
add_mem_size < best_mem_add_size) \
or (best_mem_add_size == 0 and
waste_mem_size < best_mem_waste_size):
best_mem_id = mid
......@@ -209,7 +214,7 @@ class MemoryOptimizer(object):
self.mem_ref_counter[mem_id] += 1
# de-ref input tensor mem
for idx in xrange(len(op.input)):
for idx in six.moves.range(len(op.input)):
ipt = op.input[idx]
if ipt in self.input_ref_counter:
self.input_ref_counter[ipt] -= 1
......@@ -226,8 +231,8 @@ class MemoryOptimizer(object):
print("total op: %d" % len(self.net_def.op))
print("origin mem: %d, optimized mem: %d" % (
self.get_total_origin_mem_size(),
self.get_total_optimized_mem_size()))
self.get_total_origin_mem_size(),
self.get_total_optimized_mem_size()))
class GPUMemoryOptimizer(MemoryOptimizer):
......
mace/python/tools/tf_ops_stats.py
浏览文件 @ c8d90837
......@@ -16,8 +16,10 @@ import operator
import functools
import argparse
import sys
import six
import copy
import six
import tensorflow as tf
from tensorflow import gfile
from tensorflow.core.framework import graph_pb2
......@@ -51,7 +53,7 @@ def add_shape_info(input_graph_def, input_nodes, input_shapes):
else:
idx = input_nodes.index(node.name + ':0')
input_shape = input_shapes[idx]
print input_shape
print(input_shape)
placeholder_node = copy.deepcopy(node)
placeholder_node.attr.clear()
placeholder_node.attr['shape'].shape.dim.extend([
......@@ -215,7 +217,7 @@ def main(unused_args):
def parse_args():
'''Parses command line arguments.'''
"""Parses command line arguments."""
parser = argparse.ArgumentParser()
parser.add_argument(
'--input',
......
tools/common.py
浏览文件 @ c8d90837
......@@ -15,6 +15,8 @@
import enum
import re
import six
################################
# log
......@@ -33,24 +35,24 @@ class CMDColors:
class MaceLogger:
@staticmethod
def header(message):
print CMDColors.PURPLE + message + CMDColors.ENDC
six.print_(CMDColors.PURPLE + message + CMDColors.ENDC)
@staticmethod
def summary(message):
print CMDColors.GREEN + message + CMDColors.ENDC
six.print_(CMDColors.GREEN + message + CMDColors.ENDC)
@staticmethod
def info(message):
print message
six.print_(message)
@staticmethod
def warning(message):
print CMDColors.YELLOW + 'WARNING:' + message + CMDColors.ENDC
six.print_(CMDColors.YELLOW + 'WARNING:' + message + CMDColors.ENDC)
@staticmethod
def error(module, message):
print CMDColors.RED + 'ERROR: [' + module + '] '\
+ message + CMDColors.ENDC
six.print_(CMDColors.RED + 'ERROR: [' + module + '] '
+ message + CMDColors.ENDC)
exit(1)
......@@ -71,7 +73,7 @@ class StringFormatter:
for row_idx in range(data_size):
data_tuple = data[row_idx]
ele_size = len(data_tuple)
assert(ele_size == column_size)
assert (ele_size == column_size)
for i in range(ele_size):
column_length[i] = max(column_length[i],
len(str(data_tuple[i])) + 1)
......
tools/converter.py
浏览文件 @ c8d90837
......@@ -19,12 +19,12 @@ import os
import re
import sh
import subprocess
import six
import sys
import urllib
import yaml
from enum import Enum
import six
import sh_commands
from sh_commands import BuildType
......@@ -280,7 +280,7 @@ def get_opencl_mode(configs):
def md5sum(str):
md5 = hashlib.md5()
md5.update(str)
md5.update(str.encode('utf-8'))
return md5.hexdigest()
......@@ -670,7 +670,7 @@ def get_model_files(model_file_path,
if not os.path.exists(model_file) or \
sha256_checksum(model_file) != model_sha256_checksum:
MaceLogger.info("Downloading model, please wait ...")
urllib.urlretrieve(model_file_path, model_file)
six.moves.urllib.request.urlretrieve(model_file_path, model_file)
MaceLogger.info("Model downloaded successfully.")
if sha256_checksum(model_file) != model_sha256_checksum:
......@@ -684,7 +684,7 @@ def get_model_files(model_file_path,
if not os.path.exists(weight_file) or \
sha256_checksum(weight_file) != weight_sha256_checksum:
MaceLogger.info("Downloading model weight, please wait ...")
urllib.urlretrieve(weight_file_path, weight_file)
six.moves.urllib.request.urlretrieve(weight_file_path, weight_file)
MaceLogger.info("Model weight downloaded successfully.")
if weight_file:
......@@ -955,7 +955,7 @@ def build_quantize_stat(configs):
quantize_stat_target = QUANTIZE_STAT_TARGET
build_arg = ""
print (configs[YAMLKeyword.model_graph_format])
six.print_(configs[YAMLKeyword.model_graph_format])
if configs[YAMLKeyword.model_graph_format] == ModelFormat.code:
mace_check(os.path.exists(ENGINE_CODEGEN_DIR),
ModuleName.RUN,
......@@ -1037,7 +1037,7 @@ def tuning(library_name, model_name, model_config,
model_graph_format, model_data_format,
target_abi, target_soc, serial_num,
mace_lib_type):
print('* Tuning, it may take some time...')
six.print_('* Tuning, it may take some time...')
build_tmp_binary_dir = get_build_binary_dir(library_name, target_abi)
mace_run_name = MACE_RUN_STATIC_NAME
......@@ -1107,7 +1107,7 @@ def tuning(library_name, model_name, model_config,
CL_TUNED_PARAMETER_FILE_NAME,
"%s/%s" % (model_output_dir, BUILD_TMP_OPENCL_BIN_DIR))
print('Tuning done\n')
six.print_('Tuning done\n')
def run_specific_target(flags, configs, target_abi,
......@@ -1362,8 +1362,8 @@ def run_quantize_stat(flags, configs):
stdout=subprocess.PIPE)
out, err = p.communicate()
stdout = err + out
print stdout
print("Running finished!\n")
six.print_(stdout)
six.print_("Running finished!\n")
def print_package_summary(package_path):
......
tools/falcon_cli.py
浏览文件 @ c8d90837
......@@ -15,6 +15,9 @@
import json
import socket
import itertools
import sys
import six
class FalconCli(object):
......@@ -37,15 +40,16 @@ class FalconCli(object):
buf_size=1000):
try:
return FalconCli((server, port), debug, buf_size)
except socket.error, exc:
print "error: connect to %s:%s error: %s" % (server, port, exc)
except socket.error as exc:
six.print_("error: connect to %s:%s error: %s"
% (server, port, exc), file=sys.stderr)
def call(self, name, *params):
request = dict(
id=next(self.id_counter), params=list(params), method=name)
payload = json.dumps(request).encode()
if self.debug:
print "--> req:", payload
six.print_("--> req:", payload)
self.socket_.sendall(payload)
response = self.stream.readline()
......@@ -53,7 +57,7 @@ class FalconCli(object):
raise Exception('empty response')
if self.debug:
print "<-- resp:", response
six.print_("<-- resp:", response)
response = json.loads(response.decode("utf8"))
if response.get('error') is not None:
......
tools/generate_data.py
浏览文件 @ c8d90837
......@@ -18,6 +18,8 @@ import numpy as np
import re
import common
import six
# Validation Flow:
# 1. Generate input data
# python generate_data.py \
......@@ -32,7 +34,7 @@ def generate_data(name, shape, input_file, tensor_range, input_data_type):
data = np.random.random(shape) * (tensor_range[1] - tensor_range[0]) \
+ tensor_range[0]
input_file_name = common.formatted_file_name(input_file, name)
print 'Generate input file: ', input_file_name
six.print_('Generate input file: ', input_file_name)
if input_data_type == 'float32':
np_data_type = np.float32
elif input_data_type == 'int32':
......@@ -61,7 +63,7 @@ def generate_input_data(input_file, input_node, input_shape, input_ranges,
input_range = [float(x) for x in input_ranges[i].split(',')]
generate_data(input_names[i], shape, input_file, input_range,
input_data_types[i])
print "Generate input file done."
six.print_("Generate input file done.")
def parse_args():
......
tools/sh_commands.py
浏览文件 @ c8d90837
......@@ -27,6 +27,8 @@ import urllib
import platform
from enum import Enum
import six
import common
sys.path.insert(0, "mace/python/tools")
......@@ -37,9 +39,10 @@ try:
from validate import validate
from mace_engine_factory_codegen import gen_mace_engine_factory
except Exception as e:
print("Import error:\n%s" % e)
six.print_("Import error:\n%s" % e, file=sys.stderr)
exit(1)
################################
# common
################################
......@@ -57,7 +60,7 @@ def split_stdout(stdout_str):
def make_output_processor(buff):
def process_output(line):
print(line.rstrip())
six.print_(line.rstrip())
buff.append(line)
return process_output
......@@ -95,7 +98,7 @@ def stdout_success(stdout):
stdout_lines = stdout.split("\n")
for line in stdout_lines:
if "Aborted" in line or "FAILED" in line or \
"Segmentation fault" in line:
"Segmentation fault" in line:
return False
return True
......@@ -129,7 +132,7 @@ def get_soc_serialnos_map():
soc_serialnos_map = {}
for serialno in serialnos:
props = adb_getprop_by_serialno(serialno)
soc_serialnos_map.setdefault(props["ro.board.platform"], [])\
soc_serialnos_map.setdefault(props["ro.board.platform"], []) \
.append(serialno)
return soc_serialnos_map
......@@ -178,16 +181,16 @@ def adb_get_all_socs():
def adb_push(src_path, dst_path, serialno):
print("Push %s to %s" % (src_path, dst_path))
six.print_("Push %s to %s" % (src_path, dst_path))
sh.adb("-s", serialno, "push", src_path, dst_path)
def adb_pull(src_path, dst_path, serialno):
print("Pull %s to %s" % (src_path, dst_path))
six.print_("Pull %s to %s" % (src_path, dst_path))
try:
sh.adb("-s", serialno, "pull", src_path, dst_path)
except Exception as e:
print("Error msg: %s" % e.stderr)
six.print_("Error msg: %s" % e.stderr)
def adb_run(abi,
......@@ -204,14 +207,14 @@ def adb_run(abi,
host_bin_full_path = "%s/%s" % (host_bin_path, bin_name)
device_bin_full_path = "%s/%s" % (device_bin_path, bin_name)
props = adb_getprop_by_serialno(serialno)
print(
six.print_(
"====================================================================="
)
print("Trying to lock device %s" % serialno)
six.print_("Trying to lock device %s" % serialno)
with device_lock(serialno):
print("Run on device: %s, %s, %s" %
(serialno, props["ro.board.platform"],
props["ro.product.model"]))
six.print_("Run on device: %s, %s, %s" %
(serialno, props["ro.board.platform"],
props["ro.product.model"]))
sh.adb("-s", serialno, "shell", "rm -rf %s" % device_bin_path)
sh.adb("-s", serialno, "shell", "mkdir -p %s" % device_bin_path)
adb_push(host_bin_full_path, device_bin_full_path, serialno)
......@@ -223,7 +226,7 @@ def adb_run(abi,
opencl_profiling = 1 if opencl_profiling else 0
out_of_range_check = 1 if out_of_range_check else 0
print("Run %s" % device_bin_full_path)
six.print_("Run %s" % device_bin_full_path)
stdout_buff = []
process_output = make_output_processor(stdout_buff)
......@@ -342,7 +345,7 @@ def bazel_build(target,
address_sanitizer=False,
symbol_hidden=True,
extra_args=""):
print("* Build %s with ABI %s" % (target, abi))
six.print_("* Build %s with ABI %s" % (target, abi))
if abi == "host":
bazel_args = (
"build",
......@@ -372,12 +375,12 @@ def bazel_build(target,
if symbol_hidden:
bazel_args += ("--config", "symbol_hidden")
if extra_args:
bazel_args += (extra_args, )
print bazel_args
bazel_args += (extra_args,)
six.print_(bazel_args)
sh.bazel(
_fg=True,
*bazel_args)
print("Build done!\n")
six.print_("Build done!\n")
def bazel_build_common(target, build_args=""):
......@@ -414,7 +417,7 @@ def gen_encrypted_opencl_source(codegen_path="mace/codegen"):
def gen_mace_engine_factory_source(model_tags,
embed_model_data,
codegen_path="mace/codegen"):
print("* Generate mace engine creator source")
six.print_("* Generate mace engine creator source")
codegen_tools_dir = "%s/engine" % codegen_path
sh.rm("-rf", codegen_tools_dir)
sh.mkdir("-p", codegen_tools_dir)
......@@ -423,7 +426,7 @@ def gen_mace_engine_factory_source(model_tags,
"mace/python/tools",
embed_model_data,
codegen_tools_dir)
print("Generate mace engine creator source done!\n")
six.print_("Generate mace engine creator source done!\n")
def pull_file_from_device(serial_num, file_path, file_name, output_dir):
......@@ -452,14 +455,14 @@ def merge_opencl_binaries(binaries_dirs,
if not os.path.exists(binary_path):
continue
print 'generate opencl code from', binary_path
six.print_('generate opencl code from', binary_path)
with open(binary_path, "rb") as f:
binary_array = np.fromfile(f, dtype=np.uint8)
idx = 0
size, = struct.unpack("Q", binary_array[idx:idx + 8])
idx += 8
for _ in xrange(size):
for _ in six.moves.range(size):
key_size, = struct.unpack("i", binary_array[idx:idx + 4])
idx += 4
key, = struct.unpack(
......@@ -481,7 +484,7 @@ def merge_opencl_binaries(binaries_dirs,
output_byte_array = bytearray()
data_size = len(kvs)
output_byte_array.extend(struct.pack("Q", data_size))
for key, value in kvs.iteritems():
for key, value in six.iteritems(kvs):
key_size = len(key)
output_byte_array.extend(struct.pack("i", key_size))
output_byte_array.extend(struct.pack(str(key_size) + "s", key))
......@@ -508,14 +511,14 @@ def merge_opencl_parameters(binaries_dirs,
if not os.path.exists(binary_path):
continue
print 'generate opencl parameter from', binary_path
six.print_('generate opencl parameter from', binary_path)
with open(binary_path, "rb") as f:
binary_array = np.fromfile(f, dtype=np.uint8)
idx = 0
size, = struct.unpack("Q", binary_array[idx:idx + 8])
idx += 8
for _ in xrange(size):
for _ in six.moves.range(size):
key_size, = struct.unpack("i", binary_array[idx:idx + 4])
idx += 4
key, = struct.unpack(
......@@ -529,7 +532,7 @@ def merge_opencl_parameters(binaries_dirs,
output_byte_array = bytearray()
data_size = len(kvs)
output_byte_array.extend(struct.pack("Q", data_size))
for key, value in kvs.iteritems():
for key, value in six.iteritems(kvs):
key_size = len(key)
output_byte_array.extend(struct.pack("i", key_size))
output_byte_array.extend(struct.pack(str(key_size) + "s", key))
......@@ -637,11 +640,12 @@ def gen_random_input(model_output_dir,
for i in range(len(input_file_list)):
if input_file_list[i] is not None:
dst_input_file = model_output_dir + '/' + \
common.formatted_file_name(input_file_name,
input_name_list[i])
common.formatted_file_name(input_file_name,
input_name_list[i])
if input_file_list[i].startswith("http://") or \
input_file_list[i].startswith("https://"):
urllib.urlretrieve(input_file_list[i], dst_input_file)
six.moves.urllib.request.urlretrieve(input_file_list[i],
dst_input_file)
else:
sh.cp("-f", input_file_list[i], dst_input_file)
......@@ -701,12 +705,13 @@ def tuning_run(abi,
runtime_failure_ratio=0.0,
address_sanitizer=False,
link_dynamic=False):
print("* Run '%s' with round=%s, restart_round=%s, tuning=%s, "
"out_of_range_check=%s, omp_num_threads=%s, cpu_affinity_policy=%s, "
"gpu_perf_hint=%s, gpu_priority_hint=%s" %
(model_tag, running_round, restart_round, str(tuning),
str(out_of_range_check), omp_num_threads, cpu_affinity_policy,
gpu_perf_hint, gpu_priority_hint))
six.print_("* Run '%s' with round=%s, restart_round=%s, tuning=%s, "
"out_of_range_check=%s, omp_num_threads=%s, "
"cpu_affinity_policy=%s, gpu_perf_hint=%s, "
"gpu_priority_hint=%s" %
(model_tag, running_round, restart_round, str(tuning),
str(out_of_range_check), omp_num_threads, cpu_affinity_policy,
gpu_perf_hint, gpu_priority_hint))
mace_model_path = ""
if model_graph_format == ModelFormat.file:
mace_model_path = "%s/%s.pb" % (mace_model_dir, model_tag)
......@@ -741,8 +746,8 @@ def tuning_run(abi,
stdout=subprocess.PIPE)
out, err = p.communicate()
stdout = err + out
print stdout
print("Running finished!\n")
six.print_(stdout)
six.print_("Running finished!\n")
else:
sh.adb("-s", serialno, "shell", "mkdir", "-p", phone_data_dir)
internal_storage_dir = create_internal_storage_dir(
......@@ -853,7 +858,7 @@ def tuning_run(abi,
adb_cmd_file,
_fg=True)
print("Running finished!\n")
six.print_("Running finished!\n")
return stdout
......@@ -875,7 +880,7 @@ def validate_model(abi,
input_file_name="model_input",
output_file_name="model_out",
validation_threshold=0.9):
print("* Validate with %s" % platform)
six.print_("* Validate with %s" % platform)
if abi != "host":
for output_name in output_nodes:
formatted_name = common.formatted_file_name(
......@@ -913,7 +918,7 @@ def validate_model(abi,
elif caffe_env == common.CaffeEnvType.DOCKER:
docker_image_id = sh.docker("images", "-q", image_name)
if not docker_image_id:
print("Build caffe docker")
six.print_("Build caffe docker")
sh.docker("build", "-t", image_name,
"third_party/caffe")
......@@ -925,31 +930,31 @@ def validate_model(abi,
sh.docker("rm", "-f", container_name)
container_id = ""
if not container_id:
print("Run caffe container")
six.print_("Run caffe container")
sh.docker(
"run",
"-d",
"-it",
"--name",
container_name,
image_name,
"/bin/bash")
"run",
"-d",
"-it",
"--name",
container_name,
image_name,
"/bin/bash")
for input_name in input_nodes:
formatted_input_name = common.formatted_file_name(
input_file_name, input_name)
input_file_name, input_name)
sh.docker(
"cp",
"%s/%s" % (model_output_dir, formatted_input_name),
"%s:/mace" % container_name)
"cp",
"%s/%s" % (model_output_dir, formatted_input_name),
"%s:/mace" % container_name)
for output_name in output_nodes:
formatted_output_name = common.formatted_file_name(
output_file_name, output_name)
output_file_name, output_name)
sh.docker(
"cp",
"%s/%s" % (model_output_dir, formatted_output_name),
"%s:/mace" % container_name)
"cp",
"%s/%s" % (model_output_dir, formatted_output_name),
"%s:/mace" % container_name)
model_file_name = os.path.basename(model_file_path)
weight_file_name = os.path.basename(weight_file_path)
sh.docker("cp", "tools/common.py", "%s:/mace" % container_name)
......@@ -976,22 +981,22 @@ def validate_model(abi,
"--validation_threshold=%f" % validation_threshold,
_fg=True)
print("Validation done!\n")
six.print_("Validation done!\n")
################################
# library
################################
def packaging_lib(libmace_output_dir, project_name):
print("* Package libs for %s" % project_name)
six.print_("* Package libs for %s" % project_name)
tar_package_name = "libmace_%s.tar.gz" % project_name
project_dir = "%s/%s" % (libmace_output_dir, project_name)
tar_package_path = "%s/%s" % (project_dir, tar_package_name)
if os.path.exists(tar_package_path):
sh.rm("-rf", tar_package_path)
print("Start packaging '%s' libs into %s" % (project_name,
tar_package_path))
six.print_("Start packaging '%s' libs into %s" % (project_name,
tar_package_path))
which_sys = platform.system()
if which_sys == "Linux":
sh.tar(
......@@ -1009,7 +1014,7 @@ def packaging_lib(libmace_output_dir, project_name):
"%s" % tar_package_path,
glob.glob("%s/*" % project_dir),
_fg=True)
print("Packaging Done!\n")
six.print_("Packaging Done!\n")
return tar_package_path
......@@ -1041,7 +1046,7 @@ def benchmark_model(abi,
gpu_priority_hint=3,
input_file_name="model_input",
link_dynamic=False):
print("* Benchmark for %s" % model_tag)
six.print_("* Benchmark for %s" % model_tag)
mace_model_path = ""
if model_graph_format == ModelFormat.file:
......@@ -1153,7 +1158,7 @@ def benchmark_model(abi,
adb_cmd_file,
_fg=True)
print("Benchmark done!\n")
six.print_("Benchmark done!\n")
def build_run_throughput_test(abi,
......@@ -1173,7 +1178,7 @@ def build_run_throughput_test(abi,
phone_data_dir,
strip="always",
input_file_name="model_input"):
print("* Build and run throughput_test")
six.print_("* Build and run throughput_test")
model_tag_build_flag = ""
if cpu_model_tag:
......@@ -1260,7 +1265,7 @@ def build_run_throughput_test(abi,
"--run_seconds=%s" % run_seconds,
_fg=True)
print("throughput_test done!\n")
six.print_("throughput_test done!\n")
################################
......
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