Searched refs:dim1 (Results 1 – 3 of 3) sorted by relevance
44 auto dim1 = inputPaddingTensorShape.dimensions[1]; in validate() local45 NN_RET_CHECK(!dim1 || dim1 == 2) << "Input tensor #" << kInputPaddingTensor in validate()46 << " second dimension must be 2 but is " << dim1; in validate()
527 const auto& dim1 = result.value_tuple().dimensions_value(0); in TEST() local528 EXPECT_EQ(2, dim1.field()); in TEST()529 ASSERT_EQ(2, dim1.value_tuple().dimensions_value_size()); in TEST()531 const auto& dim11 = dim1.value_tuple().dimensions_value(0); in TEST()534 const auto& dim12 = dim1.value_tuple().dimensions_value(1); in TEST()775 const auto& dim1 = result.value_tuple().dimensions_value(0); in TEST() local776 EXPECT_EQ(DimensionsValue::ValueCase::kValueTuple, dim1.value_case()); in TEST()777 ASSERT_EQ(3, dim1.value_tuple().dimensions_value_size()); in TEST()779 const auto& dim11 = dim1.value_tuple().dimensions_value(0); in TEST()783 const auto& dim12 = dim1.value_tuple().dimensions_value(1); in TEST()[all …]
255 uint32_t dim1 = 1; in calculateBroadcastedShape() local257 dim1 = getSizeOfDimension(in1, numberOfDims1 - i); in calculateBroadcastedShape()263 if (dim1 != dim2 && dim1 != 1 && dim2 != 1) { in calculateBroadcastedShape()265 << "First tensor: dimension " << numberOfDims1 - i << " of size " << dim1 in calculateBroadcastedShape()269 out->dimensions[maxDims - i] = (dim1 == 1) ? dim2 : dim1; in calculateBroadcastedShape()