chore: import upstream snapshot with attribution

tensorflow/lite/experimental/shlo/ops/exponential.cc

@@ -0,0 +1,74 @@
+/* Copyright 2024 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/lite/experimental/shlo/ops/exponential.h"
+
+#include <cmath>
+
+#include "absl/status/status.h"
+#include "tensorflow/lite/experimental/shlo/bf16.h"
+#include "tensorflow/lite/experimental/shlo/dispatch.h"
+#include "tensorflow/lite/experimental/shlo/f16.h"
+#include "tensorflow/lite/experimental/shlo/ops/unary_elementwise.h"
+#include "tensorflow/lite/experimental/shlo/ops/util.h"
+#include "tensorflow/lite/experimental/shlo/tensor.h"
+
+namespace shlo_ref {
+
+struct Exponential {
+  template <class T>
+  T operator()(T v) const {
+    return std::exp(v);
+  }
+};
+
+template <>
+F16 Exponential::operator()<F16>(F16 val) const {
+  return F16(operator()(static_cast<float>(val)));
+}
+
+template <>
+BF16 Exponential::operator()<BF16>(BF16 val) const {
+  return BF16(operator()(static_cast<float>(val)));
+}
+
+ExponentialOp Create(ExponentialOp::Attributes) { return {}; }
+
+absl::Status Prepare(ExponentialOp& op, const Tensor& input, Tensor& output) {
+  SHLO_REF_RETURN_ON_ERROR(Propagate(input.shape(), output.shape()));
+  SHLO_REF_RETURN_ON_ERROR(CheckSupportedTypes(
+      CheckCtx("cosine"), input, IsFloatTensor, IsQuantizedPerTensorTensor));
+  SHLO_REF_RETURN_ON_ERROR(
+      CheckSameBaselineType(CheckCtx("cosine"), input, output));
+  return absl::OkStatus();
+}
+
+absl::Status Evaluate(ExponentialOp& op, const Tensor& input, Tensor& output) {
+  Exponential exponential;
+  if (input.IsPerTensorQuantized()) {
+    DISPATCH_QUANTIZED(
+        detail::DequantizeOpQuantizePerTensor,
+        input.quantized_per_tensor_element_type().StorageType(),
+        input.quantized_per_tensor_element_type().ExpressedType(), exponential,
+        input, output)
+  } else if (IsFloatTensor(input)) {
+    DISPATCH_FLOAT(detail::EvaluateNoQuantization, input.tensor_element_type(),
+                   exponential, input, output);
+  }
+  return absl::FailedPreconditionError(
+      "stablehlo.tanh: Unsupported tensor type.");
+}
+
+};  // namespace shlo_ref