Home
last modified time | relevance | path

Searched refs:in_channel (Results 1 – 25 of 412) sorted by relevance

12345678910>>...17

/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/tests/python/topi/python/
H A Dtest_topi_upsampling.py30 in_channel, argument
41 A = te.placeholder((batch, in_channel, in_height, in_width), name="A")
45 in_channel,
57 in_channel,
64 size=(batch, in_channel, in_height, in_width, in_batch_block, in_channel_block)
67 A = te.placeholder((batch, in_height, in_width, in_channel), name="A")
73 in_channel,
170 in_channel, argument
181 A = te.placeholder((batch, in_channel, in_depth, in_height, in_width), name="A")
185 in_channel,
[all …]
H A Dtest_topi_conv2d_int8.py37 in_channel, argument
51 % (batch, in_channel, in_size, num_filter, kernel, stride, padding_sum, dilation)
55 A = te.placeholder((batch, in_height, in_width, in_channel), name="A", dtype="int8")
56 W = te.placeholder((kernel, kernel, in_channel, num_filter), name="W", dtype="int8")
105 in_channel, argument
119 % (batch, in_channel, in_size, num_filter, kernel, stride, padding_sum, dilation)
124 A = te.placeholder((batch, in_height, in_width, in_channel), name="A", dtype="int8")
125 W = te.placeholder((kernel, kernel, in_channel, num_filter), name="W", dtype="int8")
206 in_channel, argument
225 A = te.placeholder((batch, in_channel, in_height, in_width), name="A", dtype="int8")
[all …]
H A Dtest_topi_group_conv2d_NCHWc_int8.py42 out_channel, in_channel, kh, kw = kernel.shape
44 kernel, (out_channel // oc_bn, oc_bn, in_channel // ic_bn, ic_bn // 4, kh, kw, 4)
52 in_channel, argument
67 % (batch, in_channel, groups, in_size, num_filter, kernel, stride, padding)
84 (batch, in_channel // ic_block, in_height, in_width, ic_block), name="A", dtype="uint8"
89 in_channel // ic_block // groups,
102 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype("uint8")
103 w_np = np.random.uniform(size=(num_filter, in_channel // groups, kernel, kernel)).astype(
142 % (batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation),
H A Dtest_topi_group_conv2d.py45 in_channel, argument
63 A = te.placeholder((batch, in_channel, in_height, in_width), name="A")
120 in_channel,
139 in_channel,
161 in_channel, argument
246 in_channel,
265 in_channel,
284 in_channel, argument
302 A = te.placeholder((batch, in_height, in_width, in_channel), name="A")
359 in_channel,
[all …]
/dports/multimedia/lives/lives-3.2.0/lives-plugins/weed-plugins/
H A Dmirrors.c34 unsigned char *src = weed_get_voidptr_value(in_channel, WEED_LEAF_PIXEL_DATA, NULL); in mirrorx_process()
37 int pal = weed_get_int_value(in_channel, WEED_LEAF_CURRENT_PALETTE, NULL); in mirrorx_process()
38 int width = weed_get_int_value(in_channel, WEED_LEAF_WIDTH, NULL), hwidth; in mirrorx_process()
39 int height = weed_get_int_value(in_channel, WEED_LEAF_HEIGHT, NULL); in mirrorx_process()
40 int irowstride = weed_get_int_value(in_channel, WEED_LEAF_ROWSTRIDES, NULL); in mirrorx_process()
74 weed_plant_t *in_channel = weed_get_in_channel(inst, 0); in mirrory_process() local
76 int palette = weed_channel_get_palette(in_channel); in mirrory_process()
77 int width = weed_channel_get_width(in_channel); in mirrory_process()
78 int height = weed_channel_get_height(in_channel); in mirrory_process()
79 int irowstride = weed_channel_get_stride(in_channel); in mirrory_process()
[all …]
H A Dalien_overlay.c39 weed_plant_t *in_channel = weed_get_plantptr_value(inst, WEED_LEAF_IN_CHANNELS, NULL); in alien_over_init() local
40 int width = weed_channel_get_width(in_channel) * 3; in alien_over_init()
41 int height = weed_channel_get_height(in_channel); in alien_over_init()
78 …weed_plant_t *in_channel = weed_get_in_channel(inst, 0), *out_channel = weed_get_out_channel(inst,… in alien_over_process() local
79 unsigned char *src = weed_channel_get_pixel_data(in_channel); in alien_over_process()
84 int pal = weed_channel_get_palette(in_channel); in alien_over_process()
86 int width = weed_channel_get_width(in_channel) * psize; in alien_over_process()
87 int height = weed_channel_get_height(in_channel); in alien_over_process()
88 int irowstride = weed_channel_get_stride(in_channel); in alien_over_process()
H A Dxeffect.c47 weed_plant_t *in_channel = weed_get_in_channel(inst, 0); in xeffect_init() local
48 int width = weed_channel_get_width(in_channel); in xeffect_init()
49 int height = weed_channel_get_height(in_channel); in xeffect_init()
67 weed_plant_t *in_channel = weed_get_in_channel(inst, 0), in xeffect_process() local
69 int palette = weed_channel_get_palette(in_channel); in xeffect_process()
72 int width = weed_channel_get_width(in_channel); in xeffect_process()
74 int height = weed_channel_get_height(in_channel); in xeffect_process()
76 int irowstride = weed_channel_get_stride(in_channel); in xeffect_process()
79 unsigned char *src = weed_channel_get_pixel_data(in_channel); in xeffect_process()
H A DrevTV.c36 weed_plant_t *in_channel, *out_channel, **in_params; in revtv_process() local
49 in_channel = weed_get_plantptr_value(inst, WEED_LEAF_IN_CHANNELS, NULL); in revtv_process()
52 src = (unsigned char *)weed_get_voidptr_value(in_channel, WEED_LEAF_PIXEL_DATA, NULL); in revtv_process()
55 width = weed_get_int_value(in_channel, WEED_LEAF_WIDTH, NULL); in revtv_process()
56 height = weed_get_int_value(in_channel, WEED_LEAF_HEIGHT, NULL); in revtv_process()
58 pal = weed_get_int_value(in_channel, WEED_LEAF_CURRENT_PALETTE, NULL); in revtv_process()
60 irow = weed_get_int_value(in_channel, WEED_LEAF_ROWSTRIDES, NULL); in revtv_process()
H A Dblank_frame_detector.c63 weed_plant_t *in_channel = weed_get_plantptr_value(inst, WEED_LEAF_IN_CHANNELS, NULL); in bfd_process() local
64 …unsigned char *src = (unsigned char *)weed_get_voidptr_value(in_channel, WEED_LEAF_PIXEL_DATA, NUL… in bfd_process()
68 int width = weed_get_int_value(in_channel, WEED_LEAF_WIDTH, NULL); in bfd_process()
69 int height = weed_get_int_value(in_channel, WEED_LEAF_HEIGHT, NULL); in bfd_process()
70 int pal = weed_get_int_value(in_channel, WEED_LEAF_CURRENT_PALETTE, NULL); in bfd_process()
71 int irowstride = weed_get_int_value(in_channel, WEED_LEAF_ROWSTRIDES, NULL); in bfd_process()
82 luma = calc_luma(&src[i], pal, weed_get_int_value(in_channel, WEED_LEAF_YUV_CLAMPING, NULL)); in bfd_process()
/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/topi/x86/
H A Dconv2d_alter_op.py78 batch_size, in_channel, height, width = get_const_tuple(data_tensor.shape)
94 (out_channel // oc_bn, in_channel // ic_bn, kh, kw, ic_bn, oc_bn),
124 batch_size, in_channel, height, width = get_const_tuple(data_tensor.shape)
150 (batch_size, in_channel // ic_bn, height, width, ic_bn), dtype=data_dtype
180 batch_size, in_channel, height, width = get_const_tuple(data_tensor.shape)
313 in_channel = -1
316 in_channel = data_tensor.shape[3].value
319 in_channel = data_tensor.shape[1].value
324 if in_channel % 4 != 0:
325 new_in_channel = ((in_channel + 4) // 4) * 4
[all …]
/dports/math/libxsmm/libxsmm-1.16.3/samples/deeplearning/tvm_cnnlayer/
H A Dmb1_tuned_latest.py61 def convert_input(a_np, batch, in_channel,input_height,input_width,pad_height,pad_width,vlen,A): argument
65 for j in range(math.ceil(in_channel/vlen)):
96 def convert_weight(w_np, in_channel, out_channel, kernel_height, kernel_width, vlen,W): argument
100 for j in range(math.ceil(in_channel/vlen)):
105 if i*vlen + n >= out_channel or j*vlen + m >= in_channel:
180 if math.ceil(in_channel/ifmblock) == rco:
228 if math.ceil(in_channel/ifmblock) == rco:
247 rco1 = tvm.reduce_axis((0, math.ceil(in_channel/ifmblock)), name='rco1')
273 A2 = tvm.compute((batch, math.ceil(in_channel/ifmblock),ofh,ofw,ifmblock),
301 cfg.add_flop(np.prod(get_const_tuple(B1.shape))*in_channel*filter_height*filter_width*2)
[all …]
/dports/misc/tvm/incubator-tvm-0.6.1/topi/tests/python/
H A Dtest_topi_group_conv2d_NCHWc_int8.py40 out_channel, in_channel, kh, kw = kernel.shape
41 kernel = np.reshape(kernel, (out_channel//oc_bn, oc_bn, in_channel//ic_bn, ic_bn//4, kh, kw, 4))
45 def verify_group_conv2d_NCHWc_int8(batch, in_channel, groups, in_size, num_filter, kernel, stride, argument
49 (batch, in_channel, groups, in_size, num_filter, kernel, stride, padding))
64 …A = tvm.placeholder((batch, in_channel//ic_block, in_height, in_width, ic_block), name='A', dtype=…
65 …W = tvm.placeholder((num_filter//oc_block, in_channel//ic_block//groups, kernel, kernel, ic_block/…
69 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype("uint8")
70 … w_np = np.random.uniform(size=(num_filter, in_channel//groups, kernel, kernel)).astype("int8")
96 … (batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation))
H A Dtest_topi_resize.py26 def verify_resize(batch, in_channel, in_height, in_width, out_height, out_width, layout='NCHW', ali… argument
28 A = tvm.placeholder((batch, in_channel, in_height, in_width), name='A', dtype='float32')
30 out_shape = (batch, in_channel, out_height, out_width)
31 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype(dtype)
33 A = tvm.placeholder((batch, in_height, in_width, in_channel), name='A', dtype='float32')
35 out_shape = (batch, out_height, out_width, in_channel)
36 a_np = np.random.uniform(size=(batch, in_height, in_width, in_channel)).astype(dtype)
H A Dtest_topi_conv2d_NCHWc.py38 out_channel, in_channel, kh, kw = kernel.shape
39 kernel = np.reshape(kernel, (out_channel//oc_bn, oc_bn, in_channel//ic_bn, ic_bn, kh, kw))
50 def verify_conv2d_NCHWc(batch, in_channel, in_size, num_filter, kernel, stride, argument
53 (batch, in_channel, in_size, num_filter, kernel, stride, padding))
68 if in_channel % bn == 0:
72 A = tvm.placeholder((batch, in_channel//ic_block, in_height, in_width, ic_block), name='A')
73 …W = tvm.placeholder((num_filter//oc_block, in_channel//ic_block, kernel, kernel, ic_block, oc_bloc…
78 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype(dtype)
79 w_np = np.random.uniform(size=(num_filter, in_channel, kernel, kernel)).astype(dtype)
117 … (batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation))
[all …]
H A Dtest_topi_upsampling.py26 def verify_upsampling(batch, in_channel, in_height, in_width, scale_h, scale_w, argument
29 A = tvm.placeholder((batch, in_channel, in_height, in_width), name='A')
31 out_shape = (batch, in_channel, int(round(in_height*scale_h)), int(round(in_width*scale_w)))
32 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype(dtype)
34 A = tvm.placeholder((batch, in_height, in_width, in_channel), name='A')
36 out_shape = (batch, int(round(in_height*scale_h)), int(round(in_width*scale_w)), in_channel)
37 a_np = np.random.uniform(size=(batch, in_height, in_width, in_channel)).astype(dtype)
/dports/misc/py-tvm/incubator-tvm-0.6.1/topi/tests/python/
H A Dtest_topi_group_conv2d_NCHWc_int8.py40 out_channel, in_channel, kh, kw = kernel.shape
41 kernel = np.reshape(kernel, (out_channel//oc_bn, oc_bn, in_channel//ic_bn, ic_bn//4, kh, kw, 4))
45 def verify_group_conv2d_NCHWc_int8(batch, in_channel, groups, in_size, num_filter, kernel, stride, argument
49 (batch, in_channel, groups, in_size, num_filter, kernel, stride, padding))
64 …A = tvm.placeholder((batch, in_channel//ic_block, in_height, in_width, ic_block), name='A', dtype=…
65 …W = tvm.placeholder((num_filter//oc_block, in_channel//ic_block//groups, kernel, kernel, ic_block/…
69 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype("uint8")
70 … w_np = np.random.uniform(size=(num_filter, in_channel//groups, kernel, kernel)).astype("int8")
96 … (batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation))
H A Dtest_topi_resize.py26 def verify_resize(batch, in_channel, in_height, in_width, out_height, out_width, layout='NCHW', ali… argument
28 A = tvm.placeholder((batch, in_channel, in_height, in_width), name='A', dtype='float32')
30 out_shape = (batch, in_channel, out_height, out_width)
31 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype(dtype)
33 A = tvm.placeholder((batch, in_height, in_width, in_channel), name='A', dtype='float32')
35 out_shape = (batch, out_height, out_width, in_channel)
36 a_np = np.random.uniform(size=(batch, in_height, in_width, in_channel)).astype(dtype)
H A Dtest_topi_conv2d_NCHWc.py38 out_channel, in_channel, kh, kw = kernel.shape
39 kernel = np.reshape(kernel, (out_channel//oc_bn, oc_bn, in_channel//ic_bn, ic_bn, kh, kw))
50 def verify_conv2d_NCHWc(batch, in_channel, in_size, num_filter, kernel, stride, argument
53 (batch, in_channel, in_size, num_filter, kernel, stride, padding))
68 if in_channel % bn == 0:
72 A = tvm.placeholder((batch, in_channel//ic_block, in_height, in_width, ic_block), name='A')
73 …W = tvm.placeholder((num_filter//oc_block, in_channel//ic_block, kernel, kernel, ic_block, oc_bloc…
78 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype(dtype)
79 w_np = np.random.uniform(size=(num_filter, in_channel, kernel, kernel)).astype(dtype)
117 … (batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation))
[all …]
H A Dtest_topi_upsampling.py26 def verify_upsampling(batch, in_channel, in_height, in_width, scale_h, scale_w, argument
29 A = tvm.placeholder((batch, in_channel, in_height, in_width), name='A')
31 out_shape = (batch, in_channel, int(round(in_height*scale_h)), int(round(in_width*scale_w)))
32 a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype(dtype)
34 A = tvm.placeholder((batch, in_height, in_width, in_channel), name='A')
36 out_shape = (batch, int(round(in_height*scale_h)), int(round(in_width*scale_w)), in_channel)
37 a_np = np.random.uniform(size=(batch, in_height, in_width, in_channel)).astype(dtype)
/dports/misc/tvm/incubator-tvm-0.6.1/topi/recipe/conv/
H A Ddepthwise_conv2d_test.py51 in_channel = 256
55 filter_channel = in_channel
66 Input = tvm.placeholder((batch, in_channel, in_height, in_width), name='Input')
69 Scale = tvm.placeholder((in_channel * channel_multiplier,), name='Scale')
70 Shift = tvm.placeholder((in_channel * channel_multiplier,), name='Shift')
122 for c in range(in_channel * channel_multiplier):
140 in_channel = 256
144 filter_channel = in_channel
158 Scale = tvm.placeholder((in_channel * channel_multiplier,), name='Scale')
159 Shift = tvm.placeholder((in_channel * channel_multiplier,), name='Shift')
[all …]
/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/apps/topi_recipe/conv/
H A Ddepthwise_conv2d_test.py59 in_channel = 256
63 filter_channel = in_channel
74 Input = te.placeholder((batch, in_channel, in_height, in_width), name="Input")
79 Scale = te.placeholder((in_channel * channel_multiplier,), name="Scale")
80 Shift = te.placeholder((in_channel * channel_multiplier,), name="Shift")
144 for c in range(in_channel * channel_multiplier):
166 in_channel = 256
170 filter_channel = in_channel
186 Scale = te.placeholder((in_channel * channel_multiplier,), name="Scale")
187 Shift = te.placeholder((in_channel * channel_multiplier,), name="Shift")
[all …]
/dports/misc/py-tvm/incubator-tvm-0.6.1/topi/recipe/conv/
H A Ddepthwise_conv2d_test.py51 in_channel = 256
55 filter_channel = in_channel
66 Input = tvm.placeholder((batch, in_channel, in_height, in_width), name='Input')
69 Scale = tvm.placeholder((in_channel * channel_multiplier,), name='Scale')
70 Shift = tvm.placeholder((in_channel * channel_multiplier,), name='Shift')
122 for c in range(in_channel * channel_multiplier):
140 in_channel = 256
144 filter_channel = in_channel
158 Scale = tvm.placeholder((in_channel * channel_multiplier,), name='Scale')
159 Shift = tvm.placeholder((in_channel * channel_multiplier,), name='Shift')
[all …]
/dports/misc/py-gluoncv/gluon-cv-0.9.0/scripts/gan/stylegan/
H A Dmodules.py25 def __init__(self, in_channel, out_channel, kernel_size, padding=0): argument
28 fan_in = in_channel * kernel_size * kernel_size
51 def __init__(self, in_channel, out_channel, kernel_size, padding=0): argument
57 fan_in = in_channel * kernel_size * kernel_size
150 def __init__(self, in_channel, style_dim): argument
153 self.norm = nn.InstanceNorm(in_channels=in_channel)
154 self.style = EqualLinear(style_dim, in_channel * 2)
160 mx_params[k].data()[:in_channel] = 1
161 mx_params[k].data()[in_channel:] = 0
251 self.conv1 = ConstantInput(in_channel)
[all …]
/dports/security/libssh/libssh-0.9.6/src/
H A Dconnector.c55 ssh_channel in_channel; member
127 if (connector->in_channel != NULL) { in ssh_connector_free()
128 ssh_remove_channel_callbacks(connector->in_channel, in ssh_connector_free()
157 connector->in_channel = channel; in ssh_connector_set_in_channel()
189 connector->in_channel = NULL; in ssh_connector_set_in_fd()
335 if (connector->in_channel != NULL){ in ssh_connector_fd_out_cb()
526 if (connector->in_channel != NULL) { in ssh_connector_channel_write_wontblock_cb()
570 connector->in_channel == NULL) in ssh_connector_set_event()
605 if (connector->in_channel != NULL) { in ssh_connector_set_event()
607 ssh_channel_get_session(connector->in_channel)); in ssh_connector_set_event()
[all …]
/dports/misc/tvm/incubator-tvm-0.6.1/topi/python/topi/x86/
H A Dconv2d_alter_op.py48 batch_size, height, width, in_channel = get_const_tuple(data_tensor.shape)
51 batch_size, in_channel, height, width = get_const_tuple(data_tensor.shape)
131 in_channel//ic_bn, ic_bn))
139 in_channel // ic_bn,
164 new_kernel = tvm.placeholder((out_channel//oc_bn, in_channel//ic_bn,
267 in_channel = -1
270 in_channel = data_tensor.shape[3].value
273 in_channel = data_tensor.shape[1].value
278 if in_channel % 4 != 0:
279 new_in_channel = ((in_channel + 4) // 4) * 4
[all …]

12345678910>>...17