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  1. src/go/types/unify.go

    			return u.nify(x.elem, y.elem, emode, p)
    		}
    
    	case *Struct:
    		// Two struct types unify if they have the same sequence of fields,
    		// and if corresponding fields have the same names, their (field) types unify,
    		// and they have identical tags. Two embedded fields are considered to have the same
    		// name. Lower-case field names from different packages are always different.
    		if y, ok := y.(*Struct); ok {
    Registered: Wed Jun 12 16:32:35 UTC 2024
    - Last Modified: Tue Jun 11 16:24:39 UTC 2024
    - 27.9K bytes
    - Viewed (0)
  2. tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_restore_op.mlir

    // Test that the locs are properly set to their shared_names.
    // CHECK-LOC: "tf.VarHandleOp"() <{{{.*shared_name = "var_0".*}}}>
    // CHECK-LOC-SAME: loc("var_0")
    // CHECK-LOC: "tf.VarHandleOp"() <{{{.*shared_name = "var_1".*}}}>
    // CHECK-LOC-SAME: loc("var_1")
    }
    
    // -----
    
    // RestoreV2 op not created for `AssignVariableOp(VarHandleOp, Const)` patterns
    // in the initializer function of "init_op" type.
    
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Mon Oct 30 06:52:55 UTC 2023
    - 9.9K bytes
    - Viewed (0)
  3. docs/en/docs/deployment/concepts.md

    * There can be **multiple processes** of the **same program** running at the same time.
    
    If you check out the "task manager" or "system monitor" (or similar tools) in your operating system, you will be able to see many of those processes running.
    
    Registered: Mon Jun 17 08:32:26 UTC 2024
    - Last Modified: Thu May 02 22:37:31 UTC 2024
    - 18K bytes
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  4. tensorflow/compiler/mlir/tensorflow/analysis/side_effect_analysis.h

      // Converts from read/write state that relates ops with the same parallel id
      // to a set of last accesses for use with other parallel ids. Reads/writes
      // between parallel ids are conservatively approximated as writes.
      absl::flat_hash_set<Operation*> GetLastWrites(ResourceId resource_id);
    
      // Sets the read/write state for ops within the same parallel id.
      void SetLastWrites(ResourceId resource_id,
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Wed May 15 09:04:13 UTC 2024
    - 14.8K bytes
    - Viewed (0)
  5. tensorflow/compiler/mlir/tensorflow/tests/hoist_loop_invariant.mlir

    // readonly - another variable `%var2` has the same resource handle which is not
    // readonly.
    
    // CHECK-LABEL: readvariableop_is_not_hoisted_if_not_readonly2
    // CHECK:       [[CST_0:%.*]] = "tf.Const"
    // CHECK:       [[VAR_1:%.*]] = "tf.VarHandleOp"
    // CHECK-SAME:  "shared_name_var1"
    // CHECK:       [[VAR_2:%.*]] = "tf.VarHandleOp"
    // CHECK-SAME:  "shared_name_var1"
    // CHECK:       [[CST_1:%.*]] = "tf.Const"
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Tue Aug 22 17:12:02 UTC 2023
    - 14.2K bytes
    - Viewed (0)
  6. src/net/listen_test.go

    	{"tcp4", "::ffff:127.0.0.1"},
    
    	{"tcp6", ""},
    	{"tcp6", "::"},
    
    	{"tcp6", "::1"},
    }
    
    // TestTCPListener tests both single and double listen to a test
    // listener with same address family, same listening address and
    // same port.
    func TestTCPListener(t *testing.T) {
    	switch runtime.GOOS {
    	case "plan9":
    		t.Skipf("not supported on %s", runtime.GOOS)
    	}
    
    	for _, tt := range tcpListenerTests {
    Registered: Wed Jun 12 16:32:35 UTC 2024
    - Last Modified: Mon Sep 18 17:20:52 UTC 2023
    - 20.5K bytes
    - Viewed (0)
  7. tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir

    // CHECK:  %cst = arith.constant
    // CHECK:  %[[FQ:.*]] = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
    // CHECK:  %[[R1:.*]] = "tf.Reshape"(%[[FQ]], %cst)
    // CHECK-SAME: tensor<2x1xf32>
    // CHECK:  %[[R2:.*]] = "tf.Reshape"(%[[FQ]], %cst)
    // CHECK-SAME: tensor<2x1xf32>
    }
    
    // CHECK-LABEL: fakeQuantWithConv2D
    func.func @fakeQuantWithConv2D(tensor<256x32x32x3xf32>) -> (tensor<256x8x7x16xf32>) {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 20.4K bytes
    - Viewed (0)
  8. tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir

    // CHECK:  %cst = arith.constant
    // CHECK:  %[[FQ:.*]] = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
    // CHECK:  %[[R1:.*]] = "tf.Reshape"(%[[FQ]], %cst)
    // CHECK-SAME: tensor<2x1xf32>
    // CHECK:  %[[R2:.*]] = "tf.Reshape"(%[[FQ]], %cst)
    // CHECK-SAME: tensor<2x1xf32>
    }
    
    // CHECK-LABEL: fakeQuantWithConv2D
    func.func @fakeQuantWithConv2D(tensor<256x32x32x3xf32>) -> (tensor<256x8x7x16xf32>) {
    Registered: Sun Jun 16 05:45:23 UTC 2024
    - Last Modified: Thu May 02 09:41:17 UTC 2024
    - 22K bytes
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  9. platforms/documentation/docs/src/docs/userguide/dep-man/04-modeling-features/feature_variants.adoc

    > No two variants in a dependency graph can provide the same capability
    
    We can leverage this to ensure that Gradle fails whenever the user mis-configures dependencies.
    Consider a situation where your library supports MySQL, Postgres and MongoDB, but that it's only allowed to choose _one_ of those at the same time.
    Registered: Wed Jun 12 18:38:38 UTC 2024
    - Last Modified: Fri Dec 01 18:45:05 UTC 2023
    - 13.2K bytes
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  10. docs/en/docs/tutorial/security/oauth2-jwt.md

    ## Password hashing
    
    "Hashing" means converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.
    
    Whenever you pass exactly the same content (exactly the same password) you get exactly the same gibberish.
    
    But you cannot convert from the gibberish back to the password.
    
    ### Why use password hashing
    
    Registered: Mon Jun 17 08:32:26 UTC 2024
    - Last Modified: Mon May 20 17:37:28 UTC 2024
    - 12.7K bytes
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