Tensor description

Differential Revision: D76915254

Pull Request resolved: #11792

Author: shoumikhin

extension/apple/ExecuTorch/Exported/ExecuTorch+Tensor.swift

@@ -1095,3 +1095,10 @@ public extension Tensor {
     ))
   }
 }
+
+@available(*, deprecated, message: "This API is experimental.")
+extension Tensor: CustomStringConvertible {
+  public var description: String {
+    self.anyTensor.description
+  }
+}

extension/apple/ExecuTorch/Exported/ExecuTorchTensor.mm

@@ -17,6 +17,86 @@
 using namespace executorch::extension;
 using namespace executorch::runtime;
 
+static inline NSString *dataTypeDescription(ExecuTorchDataType dataType) {
+  switch (dataType) {
+    case ExecuTorchDataTypeByte:
+      return @"byte";
+    case ExecuTorchDataTypeChar:
+      return @"char";
+    case ExecuTorchDataTypeShort:
+      return @"short";
+    case ExecuTorchDataTypeInt:
+      return @"int";
+    case ExecuTorchDataTypeLong:
+      return @"long";
+    case ExecuTorchDataTypeHalf:
+      return @"half";
+    case ExecuTorchDataTypeFloat:
+      return @"float";
+    case ExecuTorchDataTypeDouble:
+      return @"double";
+    case ExecuTorchDataTypeComplexHalf:
+      return @"complexHalf";
+    case ExecuTorchDataTypeComplexFloat:
+      return @"complexFloat";
+    case ExecuTorchDataTypeComplexDouble:
+      return @"complexDouble";
+    case ExecuTorchDataTypeBool:
+      return @"bool";
+    case ExecuTorchDataTypeQInt8:
+      return @"qint8";
+    case ExecuTorchDataTypeQUInt8:
+      return @"quint8";
+    case ExecuTorchDataTypeQInt32:
+      return @"qint32";
+    case ExecuTorchDataTypeBFloat16:
+      return @"bfloat16";
+    case ExecuTorchDataTypeQUInt4x2:
+      return @"quint4x2";
+    case ExecuTorchDataTypeQUInt2x4:
+      return @"quint2x4";
+    case ExecuTorchDataTypeBits1x8:
+      return @"bits1x8";
+    case ExecuTorchDataTypeBits2x4:
+      return @"bits2x4";
+    case ExecuTorchDataTypeBits4x2:
+      return @"bits4x2";
+    case ExecuTorchDataTypeBits8:
+      return @"bits8";
+    case ExecuTorchDataTypeBits16:
+      return @"bits16";
+    case ExecuTorchDataTypeFloat8_e5m2:
+      return @"float8_e5m2";
+    case ExecuTorchDataTypeFloat8_e4m3fn:
+      return @"float8_e4m3fn";
+    case ExecuTorchDataTypeFloat8_e5m2fnuz:
+      return @"float8_e5m2fnuz";
+    case ExecuTorchDataTypeFloat8_e4m3fnuz:
+      return @"float8_e4m3fnuz";
+    case ExecuTorchDataTypeUInt16:
+      return @"uint16";
+    case ExecuTorchDataTypeUInt32:
+      return @"uint32";
+    case ExecuTorchDataTypeUInt64:
+      return @"uint64";
+    default:
+      return @"undefined";
+  }
+}
+
+static inline NSString *shapeDynamismDescription(ExecuTorchShapeDynamism dynamism) {
+  switch (dynamism) {
+    case ExecuTorchShapeDynamismStatic:
+      return @"static";
+    case ExecuTorchShapeDynamismDynamicBound:
+      return @"dynamicBound";
+    case ExecuTorchShapeDynamismDynamicUnbound:
+      return @"dynamicUnbound";
+    default:
+      return @"undefined";
+  }
+}
+
 NSInteger ExecuTorchSizeOfDataType(ExecuTorchDataType dataType) {
   return elementSize(static_cast<ScalarType>(dataType));
 }
@@ -150,6 +230,70 @@ - (BOOL)isEqual:(nullable id)other {
   return [self isEqualToTensor:(ExecuTorchTensor *)other];
 }
 
+- (NSString *)description {
+  std::ostringstream os;
+  os << "Tensor {";
+  os << "\n  dataType: " << dataTypeDescription(static_cast<ExecuTorchDataType>(_tensor->scalar_type())).UTF8String << ",";
+  os << "\n  shape: [";
+  const auto& sizes = _tensor->sizes();
+  for (size_t index = 0; index < sizes.size(); ++index) {
+    if (index > 0) {
+      os << ",";
+    }
+    os << sizes[index];
+  }
+  os << "],";
+  os << "\n  strides: [";
+  const auto& strides = _tensor->strides();
+  for (size_t index = 0; index < strides.size(); ++index) {
+    if (index > 0) {
+      os << ",";
+    }
+    os << strides[index];
+  }
+  os << "],";
+  os << "\n  dimensionOrder: [";
+  const auto& dim_order = _tensor->dim_order();
+  for (size_t index = 0; index < dim_order.size(); ++index) {
+    if (index > 0) {
+      os << ",";
+    }
+    os << static_cast<int>(dim_order[index]);
+  }
+  os << "],";
+  os << "\n  shapeDynamism: " << shapeDynamismDescription(static_cast<ExecuTorchShapeDynamism>(_tensor->shape_dynamism())).UTF8String << ",";
+  auto const count = _tensor->numel();
+  os << "\n  count: " << count << ",";
+  os << "\n  scalars: [";
+  ET_SWITCH_REALHBBF16_TYPES(
+    static_cast<ScalarType>(_tensor->scalar_type()),
+    nullptr,
+    "description",
+    CTYPE,
+    [&] {
+      auto const *pointer = reinterpret_cast<const CTYPE*>(_tensor->unsafeGetTensorImpl()->data());
+      auto const countToPrint = std::min(count, (ssize_t)100);
+      for (size_t index = 0; index < countToPrint; ++index) {
+        if (index > 0) {
+          os << ",";
+        }
+        if constexpr (std::is_same_v<CTYPE, int8_t> ||
+                      std::is_same_v<CTYPE, uint8_t>) {
+          os << static_cast<int>(pointer[index]);
+        } else {
+          os << pointer[index];
+        }
+      }
+      if (count > countToPrint) {
+        os << ",...";
+      }
+    }
+  );
+  os << "]";
+  os << "\n}";
+  return @(os.str().c_str());
+}
+
 @end
 
 @implementation ExecuTorchTensor (BytesNoCopy)