func.func @decompose_resource_apply_adam_non_nesterov(%arg0: tensor<f32>, %arg1: tensor<f32>, %arg2: tensor<f32>, %arg3: tensor<f32>, %arg4: tensor<f32>, %arg5: tensor<f32>, %arg6: tensor<f32>) -> () {
  "tf_device.cluster"() ({

    // CHECK-DAG: [[ONE:%.*]] = "tf.Const"() <{value = dense<1.000000e+00> : tensor<f32>}>
    // CHECK-DAG: [[VAR_HANDLE:%.*]] = "tf.VarHandleOp"()

0.059801999479532242>>, %arg2: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.031925998628139496>>, %arg3: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.056272000074386597>>, %arg4: tensor<2048x528x!quant.uniform<i8<-127:127>:f32, 0.063763998448848724>>, %arg5: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.013358999975025654>>, %arg6: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.022830000147223473>>, %arg7: tensor<2048x640x!quant.uniform<i8<-127:127>:f32, 0.032276000827550888>>, %arg8: tensor...

    %5 = tfl.add %arg2, %cst_5 {fused_activation_function = "NONE"} : tensor<i32>
    %6 = tfl.add %arg1, %cst_5 {fused_activation_function = "NONE"} : tensor<i32>
    %7 = "tfl.gather"(%0, %arg2) {axis = 0 : i32} : (tensor<4x4x3xf32>, tensor<i32>) -> tensor<4x3xf32>

func.func @f(%arg0: !tfrt.chain, %arg1: !tfrt_fallback.tf_tensor, %arg2: !tfrt_fallback.tf_tensor, %arg3: !tfrt_fallback.tf_tensor, %arg4: !tfrt_fallback.tf_tensor,
        %arg5: !tfrt_fallback.tf_tensor, %arg6: !tfrt_fallback.tf_tensor, %arg7: !tfrt_fallback.tf_tensor, %arg8: !tfrt_fallback.tf_tensor, %arg9: !tfrt_fallback.tf_tensor,

  %arg4: tensor<!tf_type.resource<tensor<64xf32>>>, %arg5: tensor<!tf_type.resource<tensor<128xf32>>>)
    -> (tensor<i64>, tensor<i32>) attributes {tf._tf_data_function = true, tf.signature.is_stateful} {

// CHECK:         }

// -----

func.func @cond_false_72730(%arg0: tensor<?x?x!tf_type.string>, %arg1: tensor<?x?x!tf_type.string>, %arg2: tensor<?x?xi32>, %arg3: tensor<?x!tf_type.string>, %arg4: tensor<?x!tf_type.string>, %arg5: tensor<?xi32>, %arg6: tensor<?xi32>) -> (tensor<?x?x!tf_type.string>, tensor<?x?x!tf_type.string>) {
    %cst = arith.constant dense<[1, 0]> : tensor<2xi32>
    %cst_0 = arith.constant dense<0> : tensor<i32>

  + No trailing period
  + Keep the title as short as possible. ideally under 76 characters or shorter
+ No Markdown
+ The first PR comment (this one) is wrapped at 76 characters, unless it's
  really needed (ASCII art, table, or long link)
+ If there is a corresponding issue, add either `Fixes #1234` or `Updates #1234`
  (the latter if this is not a complete fix) to this comment
+ If referring to a repo other than `golang/go` you can use the

  %read5 = "tf.ReadVariableOp"(%arg5) : (tensor<*x!tf_type.resource<tensor<2xf32>>>) -> tensor<2xf32>
  // CHECK-NEXT: "tf.AssignVariableOp"(%[[ARG_0]], %[[ARG_2]])
  "tf.AssignVariableOp"(%arg0, %arg2) : (tensor<*x!tf_type.resource<tensor<32xf32>>>, tensor<32xf32>) -> ()
  // CHECK-NEXT: "tf.AssignVariableOp"(%[[ARG_5]], %[[ARG_6]])

{tf._user_specified_name = "903", tf.device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0"}, %arg4: tensor<*x!tf_type.resource<tensor<1024xf32>>> {tf._user_specified_name = "905", tf.device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0"}, %arg5: tensor<*x!tf_type.resource<tensor<1024x1xf32>>> {tf._user_specified_name = "907", tf.device = "/job:tpu_host_worker/replica:0/task:0/device:CPU:0"}, %arg6: tensor<*x!tf_type.resource<tensor<i64>>> {tf._user_specified_name = "909", tf.device = "/j...

Ich zeige Ihnen einige der wichtigsten Konzepte, die Sie beim Deployment einer **FastAPI**-Anwendung wahrscheinlich berücksichtigen sollten (obwohl das meiste davon auch für jede andere Art von Webanwendung gilt).