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Searched refs:shape (Results 1 – 13 of 13) sorted by relevance

/hardware/interfaces/neuralnetworks/1.2/
Dtypes.hal242 * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
269 * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
291 * * 0: The output 4-D tensor, of shape
313 * * 0 ~ n-1: The list of n input tensors, of shape
324 * tensors. The output shape is [D0, D1, ..., sum(Daxis(i)), ..., Dm].
375 * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
378 * * 1: A 4-D tensor, of shape
383 * * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
423 * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
426 * * 1: A 4-D tensor, of shape
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DIExecutionCallback.hal47 * @param outputShapes A list of shape information of model output operands.
DIPreparedModel.hal118 * @return outputShapes A list of shape information of model output operands.
DIDevice.hal222 * the shape of the tensors, which may only be known at execution time. As
313 * the shape of the tensors, which may only be known at execution time. As
/hardware/interfaces/neuralnetworks/1.0/
Dtypes.hal147 * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
170 * * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
188 * * 0: The output 4-D tensor, of shape
208 * * 0 ~ n-1: The list of n input tensors, of shape
217 * tensors. The output shape is [D0, D1, ..., sum(Daxis(i)), ..., Dm].
250 * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
252 * * 1: A 4-D tensor, of shape
255 * * 2: A 1-D tensor, of shape [depth_out], specifying the bias.
278 * * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
280 * * 1: A 4-D tensor, of shape
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DIDevice.hal90 * the shape of the tensors, which may only be known at execution time. As
/hardware/qcom/neuralnetworks/hvxservice/1.0/
DHexagonUtils.cpp279 std::string toString(const ::android::nn::Shape& shape) { in toString() argument
280 return "Shape{.type: " + toString(shape.type) + in toString()
281 ", .dimensions: " + toString(shape.dimensions.data(), shape.dimensions.size()) + in toString()
282 ", .scale: " + std::to_string(shape.scale) + in toString()
283 ", .zeroPoint: " + std::to_string(shape.offset) + "}"; in toString()
DHexagonModel.h86 bool setShape(uint32_t operand, const Shape& shape);
DHexagonModel.cpp117 bool Model::setShape(uint32_t operand, const Shape& shape) { in setShape() argument
121 mOperands[operand].dimensions = shape.dimensions; in setShape()
/hardware/interfaces/neuralnetworks/1.1/
Dtypes.hal34 * dimensions of shape block_shape + [batch], interleaves these blocks back
148 * for each spatial dimension of the input tensor. The shape of the
175 * a grid of blocks of shape block_shape, and interleaves these blocks with
195 * >= 0. The shape of the tensor must be {M, 2}, where M is the number
210 * Removes dimensions of size 1 from the shape of a tensor.
404 * may not be known is the shape of the input tensors.
DIDevice.hal95 * the shape of the tensors, which may only be known at execution time. As
/hardware/interfaces/gnss/1.0/
DIGnssMeasurementCallback.hal569 * - if there is a distorted correlation peak shape, report that multipath
571 * - if there is no distorted correlation peak shape, report
/hardware/interfaces/renderscript/1.0/
DIContext.hal40 * the shape of the window. Any dimensions present in the type must be