| /external/tensorflow/tensorflow/core/kernels/image/ |
| D | resize_bilinear_op_gpu.cu.cc | 57 const float y_lerp = in_y - floorf(in_y); in ResizeBilinearKernel_faster() local
106 out_reg[unroll] = top + (bottom - top) * y_lerp; in ResizeBilinearKernel_faster()
136 const float y_lerp = in_y - floorf(in_y); in ResizeBilinearKernel() local
163 output[out_idx] = top + (bottom - top) * y_lerp; in ResizeBilinearKernel()
191 const float y_lerp = original_y - floorf(original_y); in ResizeBilinearGradKernel() local
202 const float dtop = (1 - y_lerp) * input_grad[in_idx]; in ResizeBilinearGradKernel()
216 const float dbottom = y_lerp * input_grad[in_idx]; in ResizeBilinearGradKernel()
272 float y_lerp = (1 - fabsf(out_y_clamped - out_y_center)); in ResizeBilinearDeterministicGradKernel() local
274 acc += static_cast<T>(input_grad[in_idx] * y_lerp * x_lerp); in ResizeBilinearDeterministicGradKernel()
304 const float y_lerp = in_y - top_y_index; in LegacyResizeBilinearKernel() local
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| D | crop_and_resize_op_gpu.cu.cc | 91 const float y_lerp = in_y - top_y_index; in CropAndResizeKernel() local
119 crops_ptr[out_idx] = top + (bottom - top) * y_lerp; in CropAndResizeKernel()
182 const float y_lerp = in_y - top_y_index; in CropAndResizeBackpropImageKernel() local
188 const float dtop = (1 - y_lerp) * grads_ptr[out_idx]; in CropAndResizeBackpropImageKernel()
202 const float dbottom = y_lerp * grads_ptr[out_idx]; in CropAndResizeBackpropImageKernel()
283 const float y_lerp = in_y - top_y_index; in CropAndResizeBackpropBoxesKernel() local
313 float image_grad_x = (1 - y_lerp) * (top_right - top_left) + in CropAndResizeBackpropBoxesKernel()
314 y_lerp * (bottom_right - bottom_left); in CropAndResizeBackpropBoxesKernel()
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| D | resize_bilinear_op.cc | 110 const float x_lerp, const float y_lerp) { in compute_lerp() argument
113 return top + (bottom - top) * y_lerp; in compute_lerp()
302 const float y_lerp = in_y - floorf(in_y); in ResizeGradCore() local
303 const float inverse_y_lerp = (1.0f - y_lerp); in ResizeGradCore()
320 T(input_grad(b, y, x, c) * y_lerp * inverse_x_lerp); in ResizeGradCore()
322 T(input_grad(b, y, x, c) * y_lerp * x_lerp); in ResizeGradCore()
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| D | crop_and_resize_op.cc | 272 const float y_lerp = in_y - top_y_index; in operator ()() local
300 crops(b, y, x, d) = top + (bottom - top) * y_lerp; in operator ()()
492 const float y_lerp = in_y - top_y_index; in operator ()() local
508 const float dtop = (1 - y_lerp) * grads(b, y, x, d); in operator ()()
513 const float dbottom = y_lerp * grads(b, y, x, d); in operator ()()
695 const float y_lerp = in_y - top_y_index; in operator ()() local
720 float image_grad_x = (1 - y_lerp) * (top_right - top_left) + in operator ()()
721 y_lerp * (bottom_right - bottom_left); in operator ()()
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| D | resize_bilinear_op_test.cc | 107 const float y_lerp = in_y - std::floor(in_y); in ResizeBilinearBaseline() local
128 output(b, y, x, c) = top + (bottom - top) * y_lerp; in ResizeBilinearBaseline()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | quantization_utils_test.cc | 827 T_CALC bottom_right, T_CALC x_lerp, T_CALC y_lerp) { in ComputeRefLerp() argument
833 const T_CALC out = top + (bottom - top) / RESOLUTION_POW * y_lerp; in ComputeRefLerp()
839 uint8 bottom_right, int16 x_lerp, int16 y_lerp) { in TestComputeLerp8x8() argument
845 int16x8_t y_lerp16x8 = To16x8(y_lerp); in TestComputeLerp8x8()
856 y_lerp); in TestComputeLerp8x8()
865 << static_cast<int>(bottom_right) << ", " << x_lerp << ", " << y_lerp in TestComputeLerp8x8()
871 int32 bottom_right, int32 x_lerp, int32 y_lerp) { in TestComputeLerp32x2() argument
877 int32x2_t y_lerp32x2 = To32x2(y_lerp); in TestComputeLerp32x2()
886 static_cast<int64>(x_lerp), static_cast<int64>(y_lerp)); in TestComputeLerp32x2()
890 << y_lerp << ", " << rets[0] << ", " << ref; in TestComputeLerp32x2()
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| D | conv_ops_fused_image_transform.cc | 133 y_lerp(other.y_lerp) {} in PerCacheLineParameters()
138 T1 y_lerp; member
153 T1 y_lerp) const { in BilinearSample()
158 return top + (bottom - top) * y_lerp; in BilinearSample()
200 result.y_lerp = static_cast<T1>(in_y - top_y_index); in CalculatePerCacheLineParameters()
533 line_params.y_lerp); in operator ()()
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| D | quantized_resize_bilinear_op_test.cc | 83 const float x_lerp, const float y_lerp, const float min, in ComputeLerpReference() argument
91 const float out = top + (bottom - top) * y_lerp; in ComputeLerpReference()
100 const float x_lerp, const float y_lerp, in ComputeLerpReference() argument
105 return top + (bottom - top) * y_lerp; in ComputeLerpReference()
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| D | quantized_resize_bilinear_op.cc | 103 const float x_lerp, const float y_lerp, in ComputeLerpReference() argument
111 const float out = top + (bottom - top) * y_lerp; in ComputeLerpReference()
124 const T_SCALE y_lerp) { in ComputeLerp() argument
131 const T_CALC out = top + (bottom - top) / RESOLUTION_MULT * y_lerp; in ComputeLerp()
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| D | quantization_utils.h | 484 const int32x2_t y_lerp) { in ComputeLerp32x2() argument
506 vmlal_s32(top_x_res, bottom_sub_top_32, y_lerp); in ComputeLerp32x2()
520 const int16x8_t y_lerp) { in ComputeLerp8x8() argument
544 vmlaq_s16(top_x_res, bottom_sub_top, y_lerp); in ComputeLerp8x8()
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