1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
|
#!/usr/bin/python
# Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from tensor_wrapping import Tensor
SYMBOLS = ['B', 'K', 'M', 'G', 'T']
def ConvertBytesToHuman(n):
n = int(n)
if n < 0:
return 0
format_str = "%(val)3.1f%(symb)s"
prefix = {}
for i, s in enumerate(SYMBOLS[1:]):
prefix[s] = 1 << (i + 1) * 10
for symbol in reversed(SYMBOLS[1:]):
if n >= prefix[symbol]:
v = float(n) / prefix[symbol]
return format_str % dict(symb=symbol, val=v)
return format_str % dict(symb=SYMBOLS[0], val=n)
class TensorPrinter(object):
def __init__(self, verbose, tensor):
self.verbose = verbose
self.tensor = tensor
def PrintInfo(self, depth_str=""):
if (self.verbose < 1):
pass
print_str = ""
if self.tensor.tensor_idx < 0:
print_str = "Tensor {0:4}".format(self.tensor.tensor_idx)
else:
buffer_idx = self.tensor.tf_tensor.Buffer()
isEmpty = "Filled"
if (self.tensor.tf_buffer.DataLength() == 0):
isEmpty = " Empty"
shape_str = self.GetShapeString()
type_name = self.tensor.type_name
shape_name = ""
if self.tensor.tf_tensor.Name() != 0:
shape_name = self.tensor.tf_tensor.Name()
memory_size = ConvertBytesToHuman(self.tensor.memory_size)
print_str = "Tensor {0:4} : buffer {1:4} | {2} | {3:7} | Memory {4:6} | Shape {5} ({6})".format(
self.tensor.tensor_idx, buffer_idx, isEmpty, type_name, memory_size,
shape_str, shape_name)
print(depth_str + print_str)
def GetShapeString(self):
if self.tensor.tf_tensor.ShapeLength() == 0:
return "Scalar"
return_string = "["
for shape_idx in range(self.tensor.tf_tensor.ShapeLength()):
if (shape_idx != 0):
return_string += ", "
return_string += str(self.tensor.tf_tensor.Shape(shape_idx))
return_string += "]"
return return_string
|
