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Results 11 - 20 of 20 for 2x3x4xi32 (0.8 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/fold_constant_transpose.mlir
// ----- // Tests that int constants are not folded. // CHECK-LABEL: transpose_int func.func @transpose_int() -> tensor<3x2xi32> { %0 = stablehlo.constant dense<0> : tensor<2x3xi32> %1 = stablehlo.transpose %0, dims = [1, 0] : (tensor<2x3xi32>) -> tensor<3x2xi32> return %1 : tensor<3x2xi32> } // CHECK: transpose // ----- // Tests that transposing an argument cannot be folded. // CHECK-LABEL: transpose_arg
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 08:06:02 UTC 2024 - 2.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize_composite_functions.mlir
func.func private @quantize_gather_fn(%arg: tensor<3x4x2xf32>) -> tensor<2x3x2x2xf32> attributes {tf._original_func_name = "main_0"} { %cst = "tf.Const"() {value = dense<1> : tensor<2x3x2xi32>} : () -> tensor<2x3x2xi32> %0 = "quantfork.stats"(%arg) {layerStats = dense<[4.00000000e-6, 9.80000000e-1]> : tensor<2xf32>} : (tensor<3x4x2xf32>) -> tensor<3x4x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 91.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize/quantize_same_scale.mlir
%7 = stablehlo.broadcast_in_dim %6, dims = [2, 1] : (tensor<1x3xf32>) -> tensor<2x3x2xf32> %8 = "quantfork.qcast"(%7) {volatile} : (tensor<2x3x2xf32>) -> tensor<2x3x2x!quant.uniform<i8:f32, 0.13170163023705575:-1>> %9 = "quantfork.dcast"(%8) : (tensor<2x3x2x!quant.uniform<i8:f32, 0.13170163023705575:-1>>) -> tensor<2x3x2xf32> return %9 : tensor<2x3x2xf32> } // CHECK: quantized_dot_general_fn_1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 35.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util_test.cc
auto build_result = BuildHloFromGraph(*graph, /*use_output_shapes=*/true); ASSERT_FALSE(build_result.ok()); EXPECT_THAT(build_result.message(), HasSubstr("op operand type 'tensor<2x3x4x5xi32>' and result type " "'tensor<1xi32>' are cast incompatible")); } } // namespace
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 25 19:54:38 UTC 2024 - 9.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
} // ----- // CHECK-LABEL: func @select_batch_static_r1 func.func @select_batch_static_r1(%arg0: tensor<i1>, %arg1: tensor<2x6x8xi32>, %arg2: tensor<2x6x8xi32>) -> tensor<2x6x8xi32> { // CHECK: mhlo.select %arg0, %arg1, %arg2 %0 = "tf.Select"(%arg0, %arg1, %arg2) : (tensor<i1>, tensor<2x6x8xi32>, tensor<2x6x8xi32>) -> tensor<2x6x8xi32> func.return %0: tensor<2x6x8xi32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/convert_tf_xla_op_to_tf_op.cc
// Examples: // * If `xla_gather_op_output_type` == tensor<*xf32>, then it returns: // tensor<*xf32>. // * If `xla_gather_op_output_type` == tensor<3x5xi32> and `collapsed_dims` == // {0}, then it returns: tensor<1x3x5xi32>. // * If `xla_gather_op_output_type` == tensor<3x5xf32> and `collapsed_dims` == // {1, 3}, then it returns: tensor<3x1x5x1xf32>. Type GetSliceOpOutputType(Type xla_gather_op_output_type,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 13.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
func.func @ConvertIdentityGatherNdOp3D(%arg0: tensor<4x3x4xf32>) -> tensor<4x3x4xf32> { %cst = arith.constant dense<[[0], [1], [2], [3]]> : tensor<4x1xi32> %0 = "tfl.gather_nd"(%arg0, %cst) : (tensor<4x3x4xf32>, tensor<4x1xi32>) -> tensor<4x3x4xf32> func.return %0 : tensor<4x3x4xf32> // CHECK-LABEL: ConvertIdentityGatherNdOp3D // CHECK-SAME: (%[[ARG:.*]]: tensor<4x3x4xf32>) -> tensor<4x3x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%0 = stablehlo.constant dense<3.000000e+00> : tensor<1x1xf32> // Input inverse scale. %1 = stablehlo.constant dense<1> : tensor<1x1xi8> // Input zero point. %2 = stablehlo.constant dense<5> : tensor<2x3xi32> // Quantized filter - the pattern expects i8 but i32 is given. %3 = stablehlo.constant dense<4> : tensor<1x3xi32> // Precalculated z1 * q2.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
// CHECK: return %[[TRANSPOSE]] // ----- // Tests that a float `stablehlo.transpose` is not converted to `tfl.transpose`. func.func @transpose_float(%arg0: tensor<2x3x4xf32>) -> tensor<4x3x2xf32> { %0 = stablehlo.transpose %arg0, dims = [2, 1, 0] : (tensor<2x3x4xf32>) -> tensor<4x3x2xf32> return %0 : tensor<4x3x2xf32> } // CHECK-LABEL: transpose_float // CHECK-NOT: tfl.transpose // CHECK: stablehlo.transpose // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 106.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
func.func private @dense_image_warp_invalid_input_shape(%arg0: tensor<2x4x4xf32>, %arg1: tensor<2x4x4x2xf32>) -> tensor<2x4x4x1xf32> attributes {tf._implements = "addons:DenseImageWarp"} // expected-warning @+1 {{Flow should be a 4D float tensor}} func.func private @dense_image_warp_invalid_flow_shape(%arg0: tensor<2x4x4x1xf32>, %arg1: tensor<2x4x4xf32>) -> tensor<2x4x4x1xf32> attributes {tf._implements = "addons:DenseImageWarp"}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0)