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Results 61 - 70 of 74 for 2x4xf32 (0.12 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/fold_broadcast.mlir
%cst0 = mhlo.constant dense<[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]> : tensor<2x3xf32> %cst1 = mhlo.constant dense<[[[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], [[7.0, 8.0, 9.0], [10.0, 11.0, 12.0]]]]> : tensor<1x2x2x3xf32> %0 = "mhlo.broadcast_in_dim"(%cst0) <{broadcast_dimensions = dense<[1, 3]> : tensor<2xi64>}> : (tensor<2x3xf32>) -> tensor<1x2x2x3xf32> %1 = mhlo.multiply %0, %cst1 : tensor<1x2x2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/lstm.json
// CHECK-DAG: %[[input_18:.*]] = "quantfork.stats"({{.*}}) <{layerStats = dense<[-8.000000e-01, 1.600000e+00]> : tensor<2xf32>}> : (tensor<1x4xf32>) -> tensor<1x4xf32> // CHECK-DAG: %[[input_19:.*]] = "quantfork.stats"({{.*}}) <{layerStats = dense<[-2.000000e+00, 4.000000e+00]> : tensor<2xf32>}> : (tensor<1x2xf32>) -> tensor<1x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 06:25:50 UTC 2024 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mark_ops_for_outside_compilation.mlir
%2:2 = "tf.RecvTPUEmbeddingActivations"() {_tpu_embedding_layer = "call1", config = "\0A\0B\0C\0D"} : () -> (tensor<2x2xf32>, tensor<4x4xf32>) "tf.SendTPUEmbeddingGradients"(%2#0, %2#1) {_tpu_embedding_layer = "call1", config = "\0A\0B\0C\0D", operandSegmentSizes = array<i32: 2, 0>} : (tensor<2x2xf32>, tensor<4x4xf32>) -> () tf_device.return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 16:22:32 UTC 2024 - 29.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize_composite_functions.mlir
%2 = "quantfork.stats"(%1) {layerStats = dense<[5.00000000e-6, 7.00000000e-1]> : tensor<2xf32>} : (tensor<1x3xf32>) -> tensor<1x3xf32> return %2 : tensor<1x3xf32> } // CHECK: func.func private @quantize_dot_general_with_bias_same_shape_fn(%[[ARG_0:.+]]: tensor<1x2xf32>) -> tensor<1x3xf32> attributes {tf._original_func_name = "main_0"}
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/cc/pre_calibration_test.cc
module attributes {} { func.func @main(%arg0: tensor<1x4xf32>) -> tensor<1x3xf32> attributes {} { %0 = stablehlo.constant dense<1.0> : tensor<4x3xf32> %1 = stablehlo.dot_general %arg0, %0, contracting_dims = [1] x [0], precision = [DEFAULT, DEFAULT] : (tensor<1x4xf32>, tensor<4x3xf32>) -> tensor<1x3xf32> return %1 : tensor<1x3xf32> } } )mlir"); ASSERT_TRUE(module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 28 21:41:08 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%9 = stablehlo.convert %2 : (tensor<2x3xi32>) -> tensor<2x3xf32> %10 = stablehlo.dot_general %8, %9, contracting_dims = [1] x [0] : (tensor<1x2xf32>, tensor<2x3xf32>) -> tensor<1x3xf32> %11 = stablehlo.convert %3 : (tensor<1x3xi32>) -> tensor<1x3xf32> %12 = stablehlo.subtract %10, %11 : tensor<1x3xf32> // q1 * q2 - z1 * q2 %13 = stablehlo.multiply %12, %4 : tensor<1x3xf32> // s1 * s2
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/quantization/tensorflow/tests/prepare_lifting.mlir
%5 = "tf.Relu6"(%y) {device = ""} : (tensor<1x3x2x2xf32>) -> tensor<1x3x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 03:24:59 UTC 2024 - 33.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/raise-target-subgraphs.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
%2 = mhlo.constant dense<6.400000e+01> : tensor<64xf32> %3 = mhlo.constant dense<3.200000e+01> : tensor<64xf32> %4 = mhlo.constant dense<5.000000e-01> : tensor<64xf32> %5 = "mhlo.iota"() <{iota_dimension = 0 : i64}> : () -> tensor<64xf32> %6 = mhlo.add %5, %4 : tensor<64xf32> %7 = mhlo.multiply %6, %3 : tensor<64xf32> %8 = mhlo.divide %7, %2 : tensor<64xf32> %9 = mhlo.floor %8 : tensor<64xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0)