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Fixed issue #483, removing enum dependancy (#485)
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@PariksheetPinjari909 @tqchen
PariksheetPinjari909 authored and tqchen committed May 29, 2018
1 parent 3865410 commit 7968e36
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Showing 2 changed files with 32 additions and 42 deletions.
69 changes: 30 additions & 39 deletions nnvm/python/nnvm/frontend/darknet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,11 @@
"""

from __future__ import absolute_import as _abs
from enum import IntEnum
import numpy as np
import tvm
from .. import symbol as _sym

class LAYERTYPE(IntEnum):
class LAYERTYPE(object):
"""Darknet LAYERTYPE Class constant."""
CONVOLUTIONAL = 0
DECONVOLUTIONAL = 1
Expand Down Expand Up @@ -36,7 +35,7 @@ class LAYERTYPE(IntEnum):
REORG = 23
BLANK = 24

class ACTIVATION(IntEnum):
class ACTIVATION(object):
"""Darknet ACTIVATION Class constant."""
LOGISTIC = 0
RELU = 1
Expand Down Expand Up @@ -323,33 +322,31 @@ def _darknet_op_not_support(inputs, attrs):
raise NotImplementedError(err)

_DARKNET_CONVERT_MAP = {
'CONVOLUTIONAL' : _darknet_conv2d,
'DECONVOLUTIONAL' : _darknet_conv2d_transpose,
'CONNECTED' : _darknet_dense,
'MAXPOOL' : _darknet_maxpooling,
'SOFTMAX' : _darknet_softmax_output,
'DROPOUT' : _darknet_dropout,
'AVGPOOL' : _darknet_avgpooling,
'BATCHNORM' : _darknet_batch_norm,
'RESHAPE' : _darknet_reshape,
'ROUTE' : _darknet_route,
'REORG' : _darknet_reorg,
'REGION' : _darknet_region,
'ACTIVATION' : _darknet_activations,
'SHORTCUT' : _darknet_shortcut,
'DETECTION' : _darknet_op_not_support,
'CROP' : _darknet_op_not_support,
'COST' : _darknet_op_not_support,
'NORMALIZATION' : _darknet_op_not_support,
'LOCAL' : _darknet_op_not_support,
'ACTIVE' : _darknet_op_not_support,
'RNN' : _darknet_op_not_support,
'GRU' : _darknet_op_not_support,
'LSTM' : _darknet_op_not_support,
'CRNN' : _darknet_op_not_support,
'NETWORK' : _darknet_op_not_support,
'XNOR' : _darknet_op_not_support,
'BLANK' : _darknet_op_not_support,
LAYERTYPE.CONVOLUTIONAL : _darknet_conv2d,
LAYERTYPE.DECONVOLUTIONAL : _darknet_conv2d_transpose,
LAYERTYPE.CONNECTED : _darknet_dense,
LAYERTYPE.MAXPOOL : _darknet_maxpooling,
LAYERTYPE.SOFTMAX : _darknet_softmax_output,
LAYERTYPE.DROPOUT : _darknet_dropout,
LAYERTYPE.AVGPOOL : _darknet_avgpooling,
LAYERTYPE.BATCHNORM : _darknet_batch_norm,
LAYERTYPE.ROUTE : _darknet_route,
LAYERTYPE.REORG : _darknet_reorg,
LAYERTYPE.REGION : _darknet_region,
LAYERTYPE.SHORTCUT : _darknet_shortcut,
LAYERTYPE.DETECTION : _darknet_op_not_support,
LAYERTYPE.CROP : _darknet_op_not_support,
LAYERTYPE.COST : _darknet_op_not_support,
LAYERTYPE.NORMALIZATION : _darknet_op_not_support,
LAYERTYPE.LOCAL : _darknet_op_not_support,
LAYERTYPE.ACTIVE : _darknet_op_not_support,
LAYERTYPE.RNN : _darknet_op_not_support,
LAYERTYPE.GRU : _darknet_op_not_support,
LAYERTYPE.LSTM : _darknet_op_not_support,
LAYERTYPE.CRNN : _darknet_op_not_support,
LAYERTYPE.NETWORK : _darknet_op_not_support,
LAYERTYPE.XNOR : _darknet_op_not_support,
LAYERTYPE.BLANK : _darknet_op_not_support,
}

def _darknet_convert_symbol(op_name, inputs, attrs):
Expand All @@ -376,7 +373,7 @@ def _darknet_convert_symbol(op_name, inputs, attrs):
if op_name in _DARKNET_CONVERT_MAP:
sym, out_name = _DARKNET_CONVERT_MAP[op_name](inputs, attrs)
else:
_darknet_raise_not_supported('Operator: ' + op_name)
_darknet_raise_not_supported('Operator type ' + str(op_name))
if out_name is None:
out_name = sym.list_output_names()[0].replace('_output', '')
return out_name, sym
Expand All @@ -397,10 +394,6 @@ def _read_memory_buffer(shape, data, dtype):
data_np[i] = data[i]
return data_np.reshape(shape)

def _get_darknet_layername(layer_type):
"""Get the layer name from the darknet enums."""
return str((LAYERTYPE(layer_type))).replace('LAYERTYPE.', '')

def _get_convolution_weights(layer, opname, params, dtype):
"""Get the convolution layer weights and biases."""
if layer.nweights == 0:
Expand Down Expand Up @@ -460,8 +453,6 @@ def _get_darknet_attrs(net, layer_num):
attr = {}
use_flatten = True
layer = net.layers[layer_num]
op_name = _get_darknet_layername(layer.type)

if LAYERTYPE.CONVOLUTIONAL == layer.type:
attr.update({'layout' : 'NCHW'})
attr.update({'pad' : str(layer.pad)})
Expand Down Expand Up @@ -551,10 +542,10 @@ def _get_darknet_attrs(net, layer_num):
attr.update({'background' : layer.background})
attr.update({'softmax' : layer.softmax})
else:
err = "Darknet layer {} is not supported in nnvm.".format(op_name)
err = "Darknet layer type {} is not supported in nnvm.".format(layer.type)
raise NotImplementedError(err)

return op_name, attr
return layer.type, attr

def _get_tvm_params_name(opname, arg_name):
"""Makes the params name for the k,v pair."""
Expand Down
5 changes: 2 additions & 3 deletions nnvm/python/nnvm/testing/darknet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,6 @@
"""
from __future__ import division
import math
from enum import IntEnum
import numpy as np
import cv2
from cffi import FFI
Expand Down Expand Up @@ -91,7 +90,7 @@ def load_image(image, resize_width, resize_height):
img = load_image_color(image)
return _letterbox_image(img, resize_width, resize_height)

class LAYERTYPE(IntEnum):
class LAYERTYPE(object):
"""Darknet LAYERTYPE Class constant."""
CONVOLUTIONAL = 0
DECONVOLUTIONAL = 1
Expand Down Expand Up @@ -119,7 +118,7 @@ class LAYERTYPE(IntEnum):
REORG = 23
BLANK = 24

class ACTIVATION(IntEnum):
class ACTIVATION(object):
"""Darknet ACTIVATION Class constant."""
LOGISTIC = 0
RELU = 1
Expand Down

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