// extra ops are used, so we detect the following patterns:
//
//
//   SpaceToBatchND -> Expand -> Conv2D -> Squeeze -> BatchToSpaceND -> BiasAdd
//
//   SpaceToBatchND -> Expand -> Conv2D -> Squeeze -> Pad -> BatchToSpaceND ->
//   BiasAdd
//
//   SpaceToBatchND -> Expand -> Conv2D -> Squeeze -> BiasAdd -> BatchToSpaceND
//
//   SpaceToBatchND -> Conv2D -> Pad -> BatchToSpaceND -> BiasAdd
//

  int num_cols = tensorType.getShape()[rank - 1];

  std::vector<Value> sliced;

  if (batch_size == 1) {
    // Batch size is 1, no splitting is required
    // Squeeze the batch dimension, i.e. reshape
    // [1, num_rows, num_cols] -> [num_rows, num_cols]
    auto reshape_op = createReshapeOp(value, {num_rows, num_cols}, element_type,
                                      loc, rewriter);

  %0 = "tfl.squeeze"(%arg0) : (tensor<?x?xf32>) -> tensor<?x?xf32>
  // CHECK: return %arg0
  func.return %0 : tensor<?x?xf32>
}

// -----

// CHECK-LABEL: @squeeze_folder
func.func @squeeze_folder(%arg0 : tensor<?x?xf32>) -> tensor<*xf32> {
  %0 = "tfl.squeeze"(%arg0) : (tensor<?x?xf32>) -> tensor<*xf32>
  // CHECK: "tfl.squeeze"
  func.return %0 : tensor<*xf32>
}

// -----

				continue
			}
			// Only clear key if there are pointers in it.
			if t.Key.Pointers() {
				if goarch.PtrSize == 8 {
					*(*unsafe.Pointer)(k) = nil
				} else {
					// There are three ways to squeeze at one or more 32 bit pointers into 64 bits.
					// Just call memclrHasPointers instead of trying to handle all cases here.
					memclrHasPointers(k, 8)
				}
			}

  PAD = 34,
  UNIDIRECTIONAL_SEQUENCE_RNN = 35,
  GATHER = 36,
  BATCH_TO_SPACE_ND = 37,
  SPACE_TO_BATCH_ND = 38,
  TRANSPOSE = 39,
  MEAN = 40,
  SUB = 41,
  DIV = 42,
  SQUEEZE = 43,
  UNIDIRECTIONAL_SEQUENCE_LSTM = 44,
  STRIDED_SLICE = 45,
  BIDIRECTIONAL_SEQUENCE_RNN = 46,
  EXP = 47,
  TOPK_V2 = 48,
  SPLIT = 49,
  LOG_SOFTMAX = 50,

  PAD = 34,
  UNIDIRECTIONAL_SEQUENCE_RNN = 35,
  GATHER = 36,
  BATCH_TO_SPACE_ND = 37,
  SPACE_TO_BATCH_ND = 38,
  TRANSPOSE = 39,
  MEAN = 40,
  SUB = 41,
  DIV = 42,
  SQUEEZE = 43,
  UNIDIRECTIONAL_SEQUENCE_LSTM = 44,
  STRIDED_SLICE = 45,
  BIDIRECTIONAL_SEQUENCE_RNN = 46,
  EXP = 47,
  TOPK_V2 = 48,
  SPLIT = 49,
  LOG_SOFTMAX = 50,

  const auto& expected_params = collected_quant_params[0];
  for (int i = 1; i < collected_quant_params.size(); ++i) {
    const auto& compared_params = collected_quant_params[i];
    // For some ops (such as Transpose or Squeeze), the quantized axis might not
    // be the same, this function only verifies the scale and zero point in
    // that case. The quantized axis should be verified in their own verifier
    // method.

### Number of Processes on the Official Docker Image

The **number of processes** on this image is **computed automatically** from the CPU **cores** available.

This means that it will try to **squeeze** as much **performance** from the CPU as possible.

You can also adjust it with the configurations using **environment variables**, etc.