Add QInt8, QUInt8, QInt32 quantized scalar types with full quantizati…

[alinpahontu2912]

…on support

• Uncomment and fix ScalarType enum entries (QInt8=12, QUInt8=13, QInt32=14)
• Fix incorrect QUInt32 name to QInt32 to match PyTorch
• Add torch.qint8, torch.quint8, torch.qint32 dtype aliases
• Add torch.is_quantized() and Tensor.is_quantized() methods
• Add IsQuantized() extension method on ScalarType

Native quantization bindings:

• Add THSTensor_quantize_per_tensor, THSTensor_quantize_per_channel (C++ and P/Invoke)
• Add THSTensor_dequantize (C++ and P/Invoke)
• Add THSTensor_q_scale, THSTensor_q_zero_point (C++ and P/Invoke)
• Add THSTensor_int_repr (C++ and P/Invoke)
• Add THSTensor_q_per_channel_scales, THSTensor_q_per_channel_zero_points, THSTensor_q_per_channel_axis (C++ and P/Invoke)

Managed API:

• Add torch.quantize_per_tensor() and torch.quantize_per_channel() static methods
• Add torch.dequantize() static method
• Add Tensor.dequantize(), Tensor.q_scale(), Tensor.q_zero_point() instance methods
• Add Tensor.int_repr() instance method
• Add Tensor.q_per_channel_scales(), Tensor.q_per_channel_zero_points(), Tensor.q_per_channel_axis() instance methods

Unit tests for all new functionality (13 tests)