Searched refs:stride (Results 76 - 100 of 337) sorted by relevance

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/frameworks/ml/nn/runtime/test/generated/models/
H A Dconv_quant8_overflow_weights_as_inputs.model.cpp14 auto stride = model->addOperand(&type3); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
H A Dconv_quant8_weights_as_inputs.model.cpp14 auto stride = model->addOperand(&type3); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
23 model->addOperation(ANEURALNETWORKS_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, act}, {op4});
H A Ddepthwise_conv2d_float_large_2_weights_as_inputs.model.cpp14 auto stride = model->addOperand(&type3); local
23 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_large_2_weights_as_inputs_relaxed.model.cpp14 auto stride = model->addOperand(&type3); local
23 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
26 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_large_weights_as_inputs.model.cpp13 auto stride = model->addOperand(&type2); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_large_weights_as_inputs_relaxed.model.cpp13 auto stride = model->addOperand(&type2); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_weights_as_inputs.model.cpp13 auto stride = model->addOperand(&type3); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_float_weights_as_inputs_relaxed.model.cpp13 auto stride = model->addOperand(&type3); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8.model.cpp13 auto stride = model->addOperand(&type2); local
26 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8_large.model.cpp13 auto stride = model->addOperand(&type2); local
26 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
29 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8_large_weights_as_inputs.model.cpp13 auto stride = model->addOperand(&type2); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv2d_quant8_weights_as_inputs.model.cpp13 auto stride = model->addOperand(&type2); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv_2d.model.cpp12 auto stride = model->addOperand(&type2); local
21 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
24 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Ddepthwise_conv_2d_quant8.model.cpp13 auto stride = model->addOperand(&type2); local
22 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
25 model->addOperation(ANEURALNETWORKS_DEPTHWISE_CONV_2D, {op1, op2, op3, pad0, pad0, pad0, pad0, stride, stride, channelMultiplier, act}, {op4});
H A Dmax_pool_float_2.model.cpp8 auto stride = model->addOperand(&type1); local
15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
22 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
H A Dmax_pool_float_2_relaxed.model.cpp8 auto stride = model->addOperand(&type1); local
15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
22 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
H A Dmax_pool_float_3.model.cpp8 auto stride = model->addOperand(&type1); local
15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
22 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu6_activation}, {output});
H A Dmax_pool_float_3_relaxed.model.cpp8 auto stride = model->addOperand(&type1); local
15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
22 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu6_activation}, {output});
H A Dmax_pool_quant8_2.model.cpp8 auto stride = model->addOperand(&type1); local
15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
22 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, activation}, {output});
H A Dmax_pool_quant8_3.model.cpp8 auto stride = model->addOperand(&type1); local
15 model->setOperandValue(stride, stride_init, sizeof(int32_t) * 1);
22 model->addOperation(ANEURALNETWORKS_MAX_POOL_2D, {i0, padding, padding, padding, padding, stride, stride, filter, filter, relu1_activation}, {output});
/frameworks/native/libs/vr/libbufferhub/
H A Dion_buffer.cpp27 uint32_t stride, uint32_t format, uint64_t usage)
28 : IonBuffer(handle, width, height, kDefaultGraphicBufferLayerCount, stride,
32 uint32_t layer_count, uint32_t stride, uint32_t format,
37 "stride=%u format=%u usage=%" PRIx64,
38 handle, width, height, layer_count, stride, format, usage);
40 Import(handle, width, height, layer_count, stride, format, usage);
46 "IonBuffer::~IonBuffer: handle=%p width=%u height=%u stride=%u "
48 handle(), width(), height(), stride(), format(), usage());
92 uint32_t layer_count, uint32_t stride, uint32_t format,
96 "stride
26 IonBuffer(buffer_handle_t handle, uint32_t width, uint32_t height, uint32_t stride, uint32_t format, uint64_t usage) argument
31 IonBuffer(buffer_handle_t handle, uint32_t width, uint32_t height, uint32_t layer_count, uint32_t stride, uint32_t format, uint64_t usage) argument
91 Reset(buffer_handle_t handle, uint32_t width, uint32_t height, uint32_t layer_count, uint32_t stride, uint32_t format, uint64_t usage) argument
101 Import(buffer_handle_t handle, uint32_t width, uint32_t height, uint32_t layer_count, uint32_t stride, uint32_t format, uint64_t usage) argument
122 Import(const int* fd_array, int fd_count, const int* int_array, int int_count, uint32_t width, uint32_t height, uint32_t layer_count, uint32_t stride, uint32_t format, uint64_t usage) argument
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/frameworks/native/opengl/libagl/
H A Ddxt.h29 void *surface, int stride, int format);
/frameworks/rs/driver/runtime/
H A Drs_sample.c84 getElementAt1(const uint8_t *p, size_t stride, int32_t x, int32_t y) { argument
85 p += y * stride;
91 getElementAt2(const uint8_t *p, size_t stride, int32_t x, int32_t y) { argument
92 p += y * stride;
99 getElementAt3(const uint8_t *p, size_t stride, int32_t x, int32_t y) { argument
100 p += y * stride;
107 getElementAt4(const uint8_t *p, size_t stride, int32_t x, int32_t y) { argument
108 p += y * stride;
115 getElementAt565(const uint8_t *p, size_t stride, int32_t x, int32_t y) { argument
116 p += y * stride;
188 getSample_A(const uint8_t *p, size_t stride, int locX, int locY, int nextX, int nextY, float w0, float w1, float w2, float w3) argument
201 getSample_L(const uint8_t *p, size_t stride, int locX, int locY, int nextX, int nextY, float w0, float w1, float w2, float w3) argument
214 getSample_LA(const uint8_t *p, size_t stride, int locX, int locY, int nextX, int nextY, float w0, float w1, float w2, float w3) argument
227 getSample_RGB(const uint8_t *p, size_t stride, int locX, int locY, int nextX, int nextY, float w0, float w1, float w2, float w3) argument
240 getSample_RGBA(const uint8_t *p, size_t stride, int locX, int locY, int nextX, int nextY, float w0, float w1, float w2, float w3) argument
252 getSample_565(const uint8_t *p, size_t stride, int locX, int locY, int nextX, int nextY, float w0, float w1, float w2, float w3) argument
323 size_t stride = alloc->mHal.drvState.lod[lod].stride; local
389 size_t stride = alloc->mHal.drvState.lod[lod].stride; local
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/frameworks/native/libs/vr/libbufferhub/include/private/dvr/
H A Dion_buffer.h17 uint32_t stride, uint32_t format, uint64_t usage);
19 uint32_t layer_count, uint32_t stride, uint32_t format,
43 uint32_t layer_count, uint32_t stride, uint32_t format,
50 uint32_t layer_count, uint32_t stride, uint32_t format,
58 uint32_t layer_count, uint32_t stride, uint32_t format,
82 uint32_t stride() const { return buffer_.get() ? buffer_->getStride() : 0; } function in class:android::dvr::IonBuffer
/frameworks/rs/driver/
H A DrsdVertexArray.cpp47 stride = 0;
53 void RsdVertexArray::Attrib::set(uint32_t type, uint32_t size, uint32_t stride, argument
61 this->stride = stride;
69 ALOGV("va %i: slot=%i name=%s buf=%i ptr=%p size=%i type=0x%x stride=0x%x norm=%i offset=0x%p",
76 mAttribs[idx].stride,
113 mAttribs[ct].stride,

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