Adrian Kuegel <******@****.***> 1648469008 -0700

  // quantization.
  bool verify_numeric = false;
  // Whether to add verification for layer by layer, or on whole model. When
  // disabled (per-layer) float and quantized ops will be run from same input
  // (output of previous quantized layer). When enabled, float and quantized ops
  // will run with respective float and quantized output of previous ops.
  bool whole_model_verify = false;

                             %arg4: tensor<1x1x64x256xf32>   // conv filter #1
                            ) -> tensor<?x256xf32> {

  // This is a simplified ResNet layer that gets input in NHWC format, converts
  // it to NCHW before padding, and does all computations in NCHW (this is the
  // default setup for ResNet model trained in fp32 on GPU).
  //

    // from DEBUGGER_TYPE_FLOAT_PER_LAYER). Each layer in the debugging model
    // has a DumpTensor, and it is used to save the entire value of outputs from
    // both the quantized and unquantized layer.
    DEBUGGER_TYPE_INT_PER_LAYER = 2;
    // DEBUGGER_TYPE_FLOAT_PER_LAYER creates a debugging model with both
    // quantized and unquantized layers. The unquantized layer's input come from

Arko Dasgupta <******@****.***> 1644279450 +0530

num_channels = 1

# Training parameters.
learning_rate = 0.001
display_step = 10
batch_size = 32

# Network parameters.
n_hidden_1 = 32  # 1st conv layer number of neurons.
n_hidden_2 = 64  # 2nd conv layer number of neurons.
n_hidden_3 = 64  # 1st fully connected layer of neurons.
flatten_size = num_features // 16 * n_hidden_2

seed = 66478


class FloatModel(tf.Module):
  """Float inference for mnist model."""

	// Guaranteed to be non-empty.
	Display []string

	// Places holds the list of stack slots where this source occurs.
	// In particular, if [a,b] is an element in Places,
	// StackSet.Stacks[a].Sources[b] points to this source.
	//
	// No stack will be referenced twice in the Places slice for a given
	// StackSource. In case of recursion, Places will contain the outer-most

  OpBuilder builder(&getContext());
  auto func_op = getOperation();

  // All TPU embedding layer related ops are annotated with
  // `_tpu_embedding_layer` attribute along with corresponding string attribute.
  // Store all tpu embedding layer related ops with value of
  // `_tpu_embedding_layer` attribute as map key.
  llvm::StringMap<Operation*> enqueue_op_map;

### Default CA Flow through istio-agent

![CA Flow](docs/ca.svg)

A single SDS request from Envoy goes through a few different layers in istio-agent.

1. First, the request is handled by the SDS server. This is mostly just an intermediate translation layer exposing
   the `SecretManager` to Envoy, without much business logic. For each resource requested by Envoy, the SDS server

	}
}

// ExecObjectLayerAPINilTest - Sets the object layer to `nil`, and calls the registered object layer API endpoint,
// and assert the error response. The purpose is to validate the API handlers response when the object layer is uninitialized.