/dports/misc/tvm/incubator-tvm-0.6.1/nnvm/tests/python/compiler/ |
H A D | test_simplify_inference.py | 30 num_newaxis=len(shape) - axis - 1 31 if num_newaxis: 32 scale = sym.expand_dims(scale, axis=1, num_newaxis=num_newaxis) 33 shift = sym.expand_dims(shift, axis=1, num_newaxis=num_newaxis)
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H A D | test_fold_axis.py | 28 x = x * sym.expand_dims(in_scale, axis=1, num_newaxis=2) 35 y = y * sym.expand_dims(out_scale, axis=1, num_newaxis=2) 39 conv_weight = conv_weight * sym.expand_dims(out_scale, axis=1, num_newaxis=3) 40 conv_weight = conv_weight * sym.expand_dims(in_scale, axis=1, num_newaxis=2) 73 x = x * sym.expand_dims(in_scale, axis=1, num_newaxis=2) 81 y = y * sym.expand_dims(out_scale, axis=1, num_newaxis=2) 85 conv_weight = conv_weight * sym.expand_dims(out_scale, axis=1, num_newaxis=3) 86 conv_weight = conv_weight * sym.expand_dims(in_scale, axis=1, num_newaxis=3) 125 y = y * sym.expand_dims(scale, axis=1, num_newaxis=1)
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/dports/misc/py-tvm/incubator-tvm-0.6.1/nnvm/tests/python/compiler/ |
H A D | test_simplify_inference.py | 30 num_newaxis=len(shape) - axis - 1 31 if num_newaxis: 32 scale = sym.expand_dims(scale, axis=1, num_newaxis=num_newaxis) 33 shift = sym.expand_dims(shift, axis=1, num_newaxis=num_newaxis)
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H A D | test_fold_axis.py | 28 x = x * sym.expand_dims(in_scale, axis=1, num_newaxis=2) 35 y = y * sym.expand_dims(out_scale, axis=1, num_newaxis=2) 39 conv_weight = conv_weight * sym.expand_dims(out_scale, axis=1, num_newaxis=3) 40 conv_weight = conv_weight * sym.expand_dims(in_scale, axis=1, num_newaxis=2) 73 x = x * sym.expand_dims(in_scale, axis=1, num_newaxis=2) 81 y = y * sym.expand_dims(out_scale, axis=1, num_newaxis=2) 85 conv_weight = conv_weight * sym.expand_dims(out_scale, axis=1, num_newaxis=3) 86 conv_weight = conv_weight * sym.expand_dims(in_scale, axis=1, num_newaxis=3) 125 y = y * sym.expand_dims(scale, axis=1, num_newaxis=1)
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/dports/misc/tvm/incubator-tvm-0.6.1/tests/python/relay/ |
H A D | test_pass_simplify_inference.py | 28 num_newaxis = len(shape) - (axis + 1) 29 if num_newaxis: 30 scale = rly.expand_dims(scale, axis=1, num_newaxis=num_newaxis) 31 shift = rly.expand_dims(shift, axis=1, num_newaxis=num_newaxis)
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H A D | test_pass_fold_scale_axis.py | 38 in_bias = relay.expand_dims(in_bias, axis=1, num_newaxis=2) 52 in_bias = relay.expand_dims(in_bias, axis=1, num_newaxis=2) 58 conv_weight , relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2)) 229 conv_weight , relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2)) 258 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 271 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 326 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 331 relay.expand_dims(squeezed_scale, axis=1, num_newaxis=3)) 398 relay.expand_dims(squeezed_scale, axis=1, num_newaxis=3)) 440 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) [all …]
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/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/tests/python/relay/ |
H A D | test_pass_simplify_inference.py | 29 num_newaxis = len(shape) - (axis + 1) 30 if num_newaxis: 31 scale = rly.expand_dims(scale, axis=1, num_newaxis=num_newaxis) 32 shift = rly.expand_dims(shift, axis=1, num_newaxis=num_newaxis)
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H A D | test_pass_fold_scale_axis.py | 75 in_bias, relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2) 79 conv_weight, relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2) 343 conv_weight, relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2) 386 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 415 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 418 conv_weight, relay.expand_dims(squeezed_scale, axis=1, num_newaxis=3) 437 out_bias, relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2) 497 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 510 conv_weight, relay.expand_dims(squeezed_scale, axis=1, num_newaxis=3) 618 conv_weight, relay.expand_dims(squeezed_scale, axis=1, num_newaxis=3) [all …]
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/dports/misc/py-tvm/incubator-tvm-0.6.1/tests/python/relay/ |
H A D | test_pass_simplify_inference.py | 28 num_newaxis = len(shape) - (axis + 1) 29 if num_newaxis: 30 scale = rly.expand_dims(scale, axis=1, num_newaxis=num_newaxis) 31 shift = rly.expand_dims(shift, axis=1, num_newaxis=num_newaxis)
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H A D | test_pass_fold_scale_axis.py | 38 in_bias = relay.expand_dims(in_bias, axis=1, num_newaxis=2) 52 in_bias = relay.expand_dims(in_bias, axis=1, num_newaxis=2) 58 conv_weight , relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2)) 229 conv_weight , relay.expand_dims(squeezed_scale, axis=1, num_newaxis=2)) 258 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 271 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 326 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) 331 relay.expand_dims(squeezed_scale, axis=1, num_newaxis=3)) 398 relay.expand_dims(squeezed_scale, axis=1, num_newaxis=3)) 440 out_bias = relay.expand_dims(out_bias, axis=1, num_newaxis=2) [all …]
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/dports/misc/tvm/incubator-tvm-0.6.1/nnvm/tests/python/frontend/onnx/model_zoo/ |
H A D | super_resolution.py | 25 …elu1 = sym.relu(conv1 + sym.expand_dims(sym.Variable(name='2', shape=(64)), axis=1, num_newaxis=2)) 27 …elu2 = sym.relu(conv2 + sym.expand_dims(sym.Variable(name='4', shape=(64)), axis=1, num_newaxis=2)) 29 …elu3 = sym.relu(conv3 + sym.expand_dims(sym.Variable(name='6', shape=(32)), axis=1, num_newaxis=2)) 31 … conv4 = conv4 + sym.expand_dims(sym.Variable(name='8', shape=(factor**2)), axis=1, num_newaxis=2)
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/dports/misc/py-tvm/incubator-tvm-0.6.1/nnvm/tests/python/frontend/onnx/model_zoo/ |
H A D | super_resolution.py | 25 …elu1 = sym.relu(conv1 + sym.expand_dims(sym.Variable(name='2', shape=(64)), axis=1, num_newaxis=2)) 27 …elu2 = sym.relu(conv2 + sym.expand_dims(sym.Variable(name='4', shape=(64)), axis=1, num_newaxis=2)) 29 …elu3 = sym.relu(conv3 + sym.expand_dims(sym.Variable(name='6', shape=(32)), axis=1, num_newaxis=2)) 31 … conv4 = conv4 + sym.expand_dims(sym.Variable(name='8', shape=(factor**2)), axis=1, num_newaxis=2)
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/dports/misc/tvm/incubator-tvm-0.6.1/topi/include/topi/nn/ |
H A D | bias_add.h | 51 int num_newaxis = data_ndim - axis - 1; in bias_add() local 52 return add(data, (num_newaxis ? expand_dims(bias, 1, num_newaxis) : bias)); in bias_add()
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/dports/misc/py-tvm/incubator-tvm-0.6.1/topi/include/topi/nn/ |
H A D | bias_add.h | 51 int num_newaxis = data_ndim - axis - 1; in bias_add() local 52 return add(data, (num_newaxis ? expand_dims(bias, 1, num_newaxis) : bias)); in bias_add()
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/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/include/tvm/topi/nn/ |
H A D | bias_add.h | 52 int num_newaxis = data_ndim - axis - 1; in bias_add() local 53 return add(data, (num_newaxis ? expand_dims(bias, 1, num_newaxis) : bias)); in bias_add()
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/dports/misc/py-tvm/incubator-tvm-0.6.1/tests/python/frontend/nnvm_to_relay/ |
H A D | test_alter_conv2d.py | 44 n01 = relay.expand_dims(bias1, axis=1, num_newaxis=2) 48 n05 = relay.expand_dims(bias2, axis=1, num_newaxis=2) 52 n09 = relay.expand_dims(bias3, axis=1, num_newaxis=2) 56 n13 = relay.expand_dims(bias4, axis=1, num_newaxis=2)
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/dports/misc/tvm/incubator-tvm-0.6.1/tests/python/frontend/nnvm_to_relay/ |
H A D | test_alter_conv2d.py | 44 n01 = relay.expand_dims(bias1, axis=1, num_newaxis=2) 48 n05 = relay.expand_dims(bias2, axis=1, num_newaxis=2) 52 n09 = relay.expand_dims(bias3, axis=1, num_newaxis=2) 56 n13 = relay.expand_dims(bias4, axis=1, num_newaxis=2)
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/dports/misc/tvm/incubator-tvm-0.6.1/python/tvm/relay/op/ |
H A D | _transform.py | 397 def _expand_dim_shape_func(data_shape, ndim, axis, num_newaxis): argument 398 out = output_tensor((ndim + num_newaxis,), "int64") 402 elif i < axis + num_newaxis: 405 out[i] = data_shape[i - num_newaxis] 415 num_newaxis = get_const_int(attrs.num_newaxis) 422 convert(num_newaxis))]
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H A D | transform.py | 80 def expand_dims(data, axis, num_newaxis=1): argument 102 return _make.expand_dims(data, axis, num_newaxis)
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/dports/misc/py-tvm/incubator-tvm-0.6.1/python/tvm/relay/op/ |
H A D | _transform.py | 397 def _expand_dim_shape_func(data_shape, ndim, axis, num_newaxis): argument 398 out = output_tensor((ndim + num_newaxis,), "int64") 402 elif i < axis + num_newaxis: 405 out[i] = data_shape[i - num_newaxis] 415 num_newaxis = get_const_int(attrs.num_newaxis) 422 convert(num_newaxis))]
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H A D | transform.py | 80 def expand_dims(data, axis, num_newaxis=1): argument 102 return _make.expand_dims(data, axis, num_newaxis)
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/dports/misc/mxnet/incubator-mxnet-1.9.0/3rdparty/tvm/python/tvm/relay/op/ |
H A D | _transform.py | 521 def _expand_dim_shape_func(data_shape, ndim, axis, num_newaxis): argument 522 out = output_tensor((ndim + num_newaxis,), "int64") 526 elif i < axis + num_newaxis: 529 out[i] = data_shape[i - num_newaxis] 540 num_newaxis = get_const_int(attrs.num_newaxis) 544 return [_expand_dim_shape_func(inputs[0], convert(ndim), convert(axis), convert(num_newaxis))]
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/dports/misc/tvm/incubator-tvm-0.6.1/topi/python/topi/ |
H A D | transform.py | 25 def expand_dims(a, axis, num_newaxis=1): argument 40 return cpp.expand_dims(a, axis, num_newaxis)
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/dports/misc/py-tvm/incubator-tvm-0.6.1/topi/python/topi/ |
H A D | transform.py | 25 def expand_dims(a, axis, num_newaxis=1): argument 40 return cpp.expand_dims(a, axis, num_newaxis)
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/dports/misc/tvm/incubator-tvm-0.6.1/nnvm/python/nnvm/top/ |
H A D | nn.py | 142 bias = topi.expand_dims(bias, axis=expand_axis, num_newaxis=2) 231 bias = topi.expand_dims(bias, axis=1, num_newaxis=2) 284 bias = topi.expand_dims(bias, axis=1, num_newaxis=2) 359 bias = topi.expand_dims(bias, axis=1, num_newaxis=2)
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