diff --git a/OperatorFormulas.html b/OperatorFormulas.html
index 67e5315..d4f6d35 100644
--- a/OperatorFormulas.html
+++ b/OperatorFormulas.html
@@ -79,8 +79,8 @@
Links
-Original document location
-GitHub repo
+Original document location
+GitHub repo
Operator Equations
@@ -834,7 +834,7 @@ Operators
? |
? |
? |
- LogicalNotLayerParams |
+ ? |
? |
? |
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@@ -4212,7 +4212,7 @@ Data Types
Categories |
Name |
WebNN |
- ONNX |
+ ONNX |
DML |
XNNPACK |
StableHLO |
@@ -5691,6 +5691,49 @@ Data Types
int64
uInt64
+https://github.com/onnx/onnx/blob/main/onnx/onnx.proto#L485
+
+message TensorProto {
+ enum DataType {
+ UNDEFINED = 0;
+ // Basic types.
+ FLOAT = 1; // float
+ UINT8 = 2; // uint8_t
+ INT8 = 3; // int8_t
+ UINT16 = 4; // uint16_t
+ INT16 = 5; // int16_t
+ INT32 = 6; // int32_t
+ INT64 = 7; // int64_t
+ STRING = 8; // string
+ BOOL = 9; // bool
+
+ // IEEE754 half-precision floating-point format (16 bits wide).
+ // This format has 1 sign bit, 5 exponent bits, and 10 mantissa bits.
+ FLOAT16 = 10;
+
+ DOUBLE = 11;
+ UINT32 = 12;
+ UINT64 = 13;
+ COMPLEX64 = 14; // complex with float32 real and imaginary components
+ COMPLEX128 = 15; // complex with float64 real and imaginary components
+
+ // Non-IEEE floating-point format based on IEEE754 single-precision
+ // floating-point number truncated to 16 bits.
+ // This format has 1 sign bit, 8 exponent bits, and 7 mantissa bits.
+ BFLOAT16 = 16;
+
+ // Non-IEEE floating-point format based on papers
+ // FP8 Formats for Deep Learning, https://arxiv.org/abs/2209.05433,
+ // 8-bit Numerical Formats For Deep Neural Networks, https://arxiv.org/pdf/2206.02915.pdf.
+ // Operators supported FP8 are Cast, CastLike, QuantizeLinear, DequantizeLinear.
+ // The computation usually happens inside a block quantize / dequantize
+ // fused by the runtime.
+ FLOAT8E4M3FN = 17; // float 8, mostly used for coefficients, supports nan, not inf
+ FLOAT8E4M3FNUZ = 18; // float 8, mostly used for coefficients, supports nan, not inf, no negative zero
+ FLOAT8E5M2 = 19; // follows IEEE 754, supports nan, inf, mostly used for gradients
+ FLOAT8E5M2FNUZ = 20; // follows IEEE 754, supports nan, inf, mostly used for gradients, no negative zero
+ }
+
Apple BNNS (Basic Neural Network Subroutines) - bnns_constants.h - https://github.com/alexey-lysiuk/macos-sdk/blob/6c1513f5b0667b76e24aaadcad130e90c545f046/MacOSX14.0.sdk/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/Headers/BNNS/bnns_constants.h#L33-L91
BNNSDataTypeFloat16 - 16-bit half precision floating point
BNNSDataTypeBFloat16 - 16-bit brain floating Point
diff --git a/Readme.md b/Readme.md
index a27cda3..95ed7c8 100644
--- a/Readme.md
+++ b/Readme.md
@@ -5,5 +5,5 @@ published-on: 2019-04-19
date: 2024-01-25
---
-- http://fdwr.github.io/LostOnnxDocs/OperatorFormulas.html
+- http://fdwr.github.io/MachineLearningOperators/OperatorFormulas.html
- [Machine Learning Ecosystem diagram](MachineLearningEcosystem.md)