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Results 1 - 10 of 74 for dims1 (0.07 sec)
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tensorflow/compiler/mlir/tensorflow/ir/tf_traits.h
return a; } int64_t rank = a.getRank(); SmallVector<int64_t, 4> dims; dims.resize(rank); for (int i = 0, e = rank; i != e; i++) { int64_t dim0 = a.getDimSize(i); int64_t dim1 = b.getDimSize(i); dims[i] = (dim0 == ShapedType::kDynamic) ? dim1 : dim0; } return RankedTensorType::get(dims, a.getElementType()); } } // namespace detail
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 12.7K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test_util.cc
constexpr int64_t dims[] = {100, 100}; constexpr int num_elements = dims[0] * dims[1]; float data[num_elements]; for (int i = 0; i < num_elements; ++i) { data[i] = 1.0f; } TF_Status* status = TF_NewStatus(); TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_FLOAT, &dims[0], sizeof(dims) / sizeof(int64_t), status);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 22:37:46 UTC 2024 - 23.5K bytes - Viewed (0) -
tensorflow/compiler/aot/codegen_test_h.golden
} float& arg0(size_t dim0, size_t dim1) { return (*static_cast<float(*)[1][2]>( arg_data(0)))[dim0][dim1]; } const float* arg0_data() const { return static_cast<const float*>(arg_data(0)); } const float& arg0(size_t dim0, size_t dim1) const { return (*static_cast<const float(*)[1][2]>( arg_data(0)))[dim0][dim1]; } int arg0_size() const {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 01:20:01 UTC 2024 - 16.6K bytes - Viewed (0) -
OWNERS_ALIASES
- mikedanese sig-auth-authorizers-reviewers: - deads2k - dims - enj - liggitt - mikedanese - ncdc - smarterclayton - sttts - thockin - wojtek-t sig-auth-certificates-approvers: - liggitt - mikedanese - smarterclayton sig-auth-certificates-reviewers: - deads2k - dims - enj - liggitt - mikedanese
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Mon May 20 23:08:03 UTC 2024 - 11.3K bytes - Viewed (0) -
tensorflow/c/tf_tensor.cc
static char empty; int64_t nelems = 1; std::vector<int64_t> dims; auto shape_dims = shape.dims(); dims.reserve(shape_dims); for (int i = 0; i < shape_dims; ++i) { dims.push_back(shape.dim_size(i)); nelems *= shape.dim_size(i); } CHECK_EQ(nelems, 0); return TF_NewTensor( dtype, reinterpret_cast<const int64_t*>(dims.data()), shape.dims(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 21:57:32 UTC 2024 - 11.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
%1 = stablehlo.transpose %arg0, dims = [0, 3, 1, 2] : (tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32> %2 = stablehlo.add %1, %0 : tensor<1x4x3x3xf32> return %2 : tensor<1x4x3x3xf32> } // CHECK-SAME: (%[[ARG_0:.+]]: tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32> // CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 14.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/pipelines/process_nchw_tensor.mlir
// CHECK-DAG: %[[BIAS_CONST:.+]] = stablehlo.constant {{.*}} : tensor<4xf32> // CHECK-DAG: %[[BROADCAST_IN_DIM:.+]] = stablehlo.broadcast_in_dim %[[BIAS_CONST]], dims = [1] : (tensor<4xf32>) -> tensor<1x4x5x5xf32> // CHECK-DAG: %[[TRANSPOSE_0:.+]] = stablehlo.transpose %[[ARG]], dims = [0, 2, 3, 1] : (tensor<1x2x5x5xf32>) -> tensor<1x5x5x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 12.6K bytes - Viewed (0) -
platforms/software/platform-base/src/test/groovy/org/gradle/platform/base/internal/DefaultBinaryNamingSchemeTest.groovy
def original = createNamingScheme("parent", "type", ["dim1"]) expect: original.getOutputDirectory(new File(".")) == new File(".", "parent/type/dim1") original.withComponentName("other").getOutputDirectory(new File(".")) == new File(".", "other/type/dim1") original.withBinaryType("other").getOutputDirectory(new File(".")) == new File(".", "parent/other/dim1")
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Wed Oct 11 12:16:09 UTC 2023 - 10K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental_test.cc
*/ // Build an abstract input tensor. int64_t dims[] = {2, 2}; // Matrices will be 2 x 2 int num_dims = sizeof(dims) / sizeof(dims[0]); float vals[] = {0.0f, 0.0f, 0.0f, 0.0f}; TFE_Context* eager_ctx = TF_ExecutionContextGetTFEContext(ctx, status.get()); TFE_TensorHandle* t = TestMatrixTensorHandleWithInput(eager_ctx, vals, dims, num_dims);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 19 21:44:52 UTC 2023 - 39.1K bytes - Viewed (0) -
tensorflow/c/c_api_experimental.cc
std::vector<DimensionHandle> dims; const TF_ShapeAndType& input_shape = input_shapes->items[i]; if (input_shape.num_dims == InferenceContext::kUnknownRank) { c.SetInput(i, c.UnknownShape()); continue; } dims.reserve(input_shape.num_dims); for (int j = 0; j < input_shape.num_dims; ++j) { dims.push_back(c.MakeDim(input_shape.dims[j])); } c.SetInput(i, c.MakeShape(dims));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 29.4K bytes - Viewed (0)