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Results 1 - 8 of 8 for 512x512xf32 (0.14 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq.mlir
func.func @lift_float_matmul(%arg0: tensor<1x12x12x512xf32>) -> (tensor<*xf32>, tensor<*xf32>) { %cst = "tf.Const"() {value = dense<0.000000e+00> : tensor<512x512xf32>} : () -> tensor<512x512xf32> %out_1 = "tf.MatMul"(%arg0, %cst) { device = "", transpose_a = false, transpose_b = false } : (tensor<1x12x12x512xf32>, tensor<512x512xf32>) -> tensor<*xf32> %out_2 = "tf.MatMul"(%arg0, %arg0) { device = "", transpose_a = false, transpose_b = true
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_weights.mlir
%cst = "tf.Const"() {device = "", value = dense<1.000000e+01> : tensor<512x512xf32>} : () -> tensor<512x512xf32> %cst_sharded = "tf.XlaSharding"(%cst) {_XlaSharding = "\08\03\1A\03\01\04\02\22\08\00\04\01\05\02\06\03\070\01", device = "", sharding = "\08\03\1A\03\01\04\02\22\08\00\04\01\05\02\06\03\070\01", unspecified_dims = []} : (tensor<512x512xf32>) -> tensor<512x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 42K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/analysis/cost_analysis.mlir
// expected-remark@+1 {{Cost: 2}} %1 = "tf.ReadVariableOp"(%0) {device = "/job:localhost/replica:0/task:0/device:CPU:0"} : (tensor<!tf_type.resource<tensor<512x512xf32>>>) -> tensor<512x512xf32> // 262657 = 1 + 512 + 512 * 512 // expected-remark@+1 {{Cost: 262657}}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Aug 14 15:35:49 UTC 2023 - 12.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/optimize.mlir
// CHECK-LABEL: testDotToDotGeneralMatrixMatrix func.func @testDotToDotGeneralMatrixMatrix(%arg0: tensor<2x3072xf32>, %arg1: tensor<3072x512xf32>) -> tensor<2x512xf32> { %0 = "mhlo.dot"(%arg0, %arg1) : (tensor<2x3072xf32>, tensor<3072x512xf32>) -> tensor<2x512xf32> func.return %0 : tensor<2x512xf32> // CHECK: %[[RES:.*]] = "mhlo.dot_general"(%arg0, %arg1) <{ // CHECK-SAME: dot_dimension_numbers = #mhlo.dot<
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 22.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-dynamic-range.mlir
%w = arith.constant dense<127.0> : tensor<512x12xf32> %b = arith.constant dense<0.0> : tensor<512xf32> %fc = "tfl.fully_connected"(%0, %w, %b) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x224x224x3xf32>, tensor<512x12xf32>, tensor<512xf32>) -> tensor<1x112x112x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 38.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/get-alternative-subgraph.mlir
// CHECK: %[[VAL_11:.*]] = "tfl.reshape"(%[[VAL_9]], %[[VAL_6]]) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<384x512xf32>, tensor<4xi32>) -> tensor<1x1x384x512xf32> // CHECK: %[[VAL_12:.*]] = "tfl.reshape"(%[[VAL_10]], %[[VAL_7]]) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<128x512xf32>, tensor<4xi32>) -> tensor<128x1x1x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-dynamic-range.mlir
%w = arith.constant dense<127.0> : tensor<512x12xf32> %b = arith.constant dense<0.0> : tensor<512xf32> %fc = "tfl.fully_connected"(%arg0, %w, %b) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x224x224x3xf32>, tensor<512x12xf32>, tensor<512xf32>) -> tensor<1x112x112x512xf32> func.return %fc : tensor<1x112x112x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 23 21:09:00 UTC 2024 - 23.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
%cst_input = arith.constant dense<1.0> : tensor<2x512xf32> %cst_weights = arith.constant dense<2.0> : tensor<1024x512xf32> %cst_bias = arith.constant dense<4.0> : tensor<1024xf32> %0 = "tfl.fully_connected" (%cst_input, %cst_weights, %cst_bias) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<2x512xf32>, tensor<1024x512xf32>, tensor<1024xf32>) -> tensor<2x1024xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 45.8K bytes - Viewed (0)