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Searched refs:inputShape (Results 1 – 2 of 2) sorted by relevance

/hardware/qcom/neuralnetworks/hvxservice/1.0/
DHexagonOperationsCheck.cpp158 const Shape inputShape = model->getShape(ins[0]); in conv_2d() local
180 getPadding(inputShape.dimensions[2], inputShape.dimensions[1], stride_width, in conv_2d()
189 nn::calculateExplicitPadding(inputShape.dimensions[2], stride_width, in conv_2d()
192 nn::calculateExplicitPadding(inputShape.dimensions[1], stride_height, in conv_2d()
200 convPrepare(inputShape, filterShape, biasShape, padding_left, padding_right, padding_top, in conv_2d()
218 const Shape inputShape = model->getShape(ins[0]); in depthwise_conv_2d() local
240 getPadding(inputShape.dimensions[2], inputShape.dimensions[1], stride_width, in depthwise_conv_2d()
250 nn::calculateExplicitPadding(inputShape.dimensions[2], stride_width, in depthwise_conv_2d()
253 nn::calculateExplicitPadding(inputShape.dimensions[1], stride_height, in depthwise_conv_2d()
261 depthwiseConvPrepare(inputShape, filterShape, biasShape, padding_left, padding_right, in depthwise_conv_2d()
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DHexagonOperationsPrepare.cpp78 const Shape inputShape = model->getShape(ins[0]); in average_pool_2d() local
79 pad = getPadding(inputShape.dimensions[2], inputShape.dimensions[1], stride_width, in average_pool_2d()
149 const Shape inputShape = model->getShape(ins[0]); in conv_2d() local
151 pad = getPadding(inputShape.dimensions[2], inputShape.dimensions[1], stride_width, in conv_2d()
199 const Shape inputShape = model->getShape(ins[0]); in depthwise_conv_2d() local
201 pad = getPadding(inputShape.dimensions[2], inputShape.dimensions[1], stride_width, in depthwise_conv_2d()
266 const Shape inputShape = model->getShape(ins[0]); in l2_pool_2d() local
267 pad = getPadding(inputShape.dimensions[2], inputShape.dimensions[1], stride_width, in l2_pool_2d()
350 const Shape inputShape = model->getShape(ins[0]); in max_pool_2d() local
351 pad = getPadding(inputShape.dimensions[2], inputShape.dimensions[1], stride_width, in max_pool_2d()
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