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Results 1 - 3 of 3 for 1x1024x128 (0.24 sec)

  1. tensorflow/compiler/mlir/lite/transforms/optimize_patterns.td

      // Move binary op batched RHS before reshape:
      // binary(reshape(lhs), rhs) => reshape(binary(lhs, flatten(rhs)))
      // Pattern targetted here is as follows-
      // [input, lhr, rhs] == [<1x1024x128>, <1x1024x8x16>, <1x1x8x16xf32>]
      // This is valid only when the-
      // 1.last dimension of lhs is equal to the number of elements in constant rhs.
      // 2.Reduded shape of rhs, here <8x16> is equal to last dimensions of lhs.
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 16 20:31:41 UTC 2024
    - 66.4K bytes
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  2. tensorflow/compiler/mlir/quantization/stablehlo/tests/components/post_calibration_component.mlir

    // Tests that the dot_general accepts i8 tensors and outputs an i32 tensor.
    // Note: Argument quantization sequence omitted.
    // CHECK: stablehlo.dot_general %{{.+}}, %{{.+}}, contracting_dims = [1] x [0] : (tensor<1x1024xi8>, tensor<1024x3xi8>) -> tensor<1x3xi32>
    
    // Note: Result dequantization sequence omitted.
    // CHECK: return %{{.+}} : tensor<1x3xf32>
    
    // -----
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu Apr 25 01:09:50 UTC 2024
    - 6.7K bytes
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  3. tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops.mlir

        %4 = "tf.Cast"(%3) {Truncate = false, device = ""} : (tensor<1x1024xf32>) -> tensor<1x1024xi8>
        %5 = "tf.Cast"(%4) {Truncate = false, device = ""} : (tensor<1x1024xi8>) -> tensor<1x1024xi32>
        %6 = "tf.Sub"(%5, %cst_4) {device = ""} : (tensor<1x1024xi32>, tensor<i32>) -> tensor<1x1024xi32>
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 81K bytes
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