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Results 1 - 4 of 4 for 3x3x1x5xf32 (0.13 sec)
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tensorflow/compiler/mlir/lite/tests/push-tpose-through-ewise.mlir
// CHECK: %0 = tfl.sub %arg0, %cst_0 {fused_activation_function = "NONE"} : tensor<2x3x4x5xf32> // CHECK: %1 = "tfl.transpose"(%0, %cst) : (tensor<2x3x4x5xf32>, tensor<4xi32>) -> tensor<5x2x3x4xf32> // CHECK: return %1 : tensor<5x2x3x4xf32> // ----- // CHECK-LABEL: permNotConstNoChange func.func @permNotConstNoChange(%arg0: tensor<2x3x4x5xf32>, %perm: tensor<4xi32>) -> tensor<5x2x3x4xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 8.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver_test.cc
%cst_0 = arith.constant dense<1.0> : tensor<3x1x1x3xf32> %cst_1 = arith.constant dense<2.0> : tensor<3xf32> %0 = "tf.XlaCallModule"(%arg0, %cst_0, %cst_1) <{Sout = [#tf_type.shape<1x4x4x3>], module = "", version = 9 : i64}> {_entry_function = @composite_fn_1, _original_entry_function = "composite_fn_1", _tfl_quant_trait = "fully_quantizable"} : (tensor<1x4x4x3xf32>, tensor<3x1x1x3xf32>, tensor<3xf32>) -> tensor<1x4x4x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_legacy.mlir
// CHECK-LABEL: conv2d_backprop_input_with_add func.func @conv2d_backprop_input_with_add(%arg0: tensor<4xi32>, %arg1: tensor<3x3x1x32xf32>, %arg2: tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32> { %0 = "tf.Conv2DBackpropInput"(%arg0, %arg1, %arg2) {strides = [1, 2, 2, 1], padding="SAME", dilations=[1, 1, 1, 1]}: (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/pre_calibration_component.mlir
// Contains the `stablehlo.transpose` op of the arg (e.g. [b, f, 0, 1] to // [b, 0, 1, f]). The weight constant is folded into [0, 1, i, o] format. // CHECK-DAG: %[[CST:.+]] = stablehlo.constant dense<3.000000e+00> : tensor<3x3x8x8xf32> // CHECK: %[[TRANSPOSE_1:.+]] = stablehlo.transpose %arg0, dims = [0, 2, 3, 1] : (tensor<1x8x4x4xf32>) -> tensor<1x4x4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 5.1K bytes - Viewed (0)