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update readme

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George Hotz
2023-05-26 06:10:41 +00:00
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@@ -121,24 +121,6 @@ from tinygrad.tensor import Tensor
(Tensor.ones(4,4).gpu() + Tensor.ones(4,4).gpu()).cpu() (Tensor.ones(4,4).gpu() + Tensor.ones(4,4).gpu()).cpu()
``` ```
### ANE Support?! (broken)
If all you want to do is ReLU, you are in luck! You can do very fast ReLU (at least 30 MEGAReLUs/sec confirmed)
Requires your Python to be signed with `ane/lib/sign_python.sh` to add the `com.apple.ane.iokit-user-access` entitlement, which also requires `sudo nvram boot-args="amfi_get_out_of_my_way=1 ipc_control_port_options=0"`. Build the library with `ane/lib/build.sh`
In order to set boot-args and for the AMFI kext to respect that arg, run `csrutil enable --without-kext --without-nvram` in recovery mode.
```python
from tinygrad.tensor import Tensor
a = Tensor([-2,-1,0,1,2]).ane()
b = a.relu()
print(b.cpu())
```
Warning: do not rely on the ANE port. It segfaults sometimes. So if you were doing something important with tinygrad and wanted to use the ANE, you might have a bad time.
### hlops (in tensor.py) ### hlops (in tensor.py)
hlops are syntactic sugar around mlops. They support most things torch does. hlops are syntactic sugar around mlops. They support most things torch does.
@@ -148,7 +130,7 @@ hlops are syntactic sugar around mlops. They support most things torch does.
mlops are mid level ops. They understand derivatives. They are very simple. mlops are mid level ops. They understand derivatives. They are very simple.
``` ```
Relu, Log, Exp # unary ops Relu, Log, Exp, Sin # unary ops
Sum, Max # reduce ops (with axis argument) Sum, Max # reduce ops (with axis argument)
Maximum, Add, Sub, Mul, Pow, Div, Equal # binary ops (no broadcasting, use expand) Maximum, Add, Sub, Mul, Pow, Div, Equal # binary ops (no broadcasting, use expand)
Expand, Reshape, Permute, Pad, Shrink, Flip # movement ops Expand, Reshape, Permute, Pad, Shrink, Flip # movement ops
@@ -162,7 +144,7 @@ The autodiff stuff is all in mlops now so you can focus on the raw operations
``` ```
Buffer # class of memory on this device Buffer # class of memory on this device
unary_op (NOOP, EXP, LOG, CAST) # A -> A unary_op (NOOP, EXP, LOG, CAST, SIN) # A -> A
reduce_op (SUM, MAX) # A -> B (smaller size, B has 1 in shape) reduce_op (SUM, MAX) # A -> B (smaller size, B has 1 in shape)
binary_op (ADD, SUB, MUL, DIV, POW, CMPEQ, MAX) # A + A -> A (all the same size) binary_op (ADD, SUB, MUL, DIV, POW, CMPEQ, MAX) # A + A -> A (all the same size)
movement_op (EXPAND, RESHAPE, PERMUTE, PAD, SHRINK, STRIDE) # A -> B (different size) movement_op (EXPAND, RESHAPE, PERMUTE, PAD, SHRINK, STRIDE) # A -> B (different size)
@@ -174,16 +156,16 @@ fused_op [[optional]] (MULACC) # A * A -> B
Despite being tiny, tinygrad supports the full EfficientNet. Pass in a picture to discover what it is. Despite being tiny, tinygrad supports the full EfficientNet. Pass in a picture to discover what it is.
```bash ```bash
ipython3 examples/efficientnet.py https://media.istockphoto.com/photos/hen-picture-id831791190 python3 examples/efficientnet.py https://media.istockphoto.com/photos/hen-picture-id831791190
``` ```
Or, if you have a webcam and cv2 installed Or, if you have a webcam and cv2 installed
```bash ```bash
ipython3 examples/efficientnet.py webcam python3 examples/efficientnet.py webcam
``` ```
PROTIP: Set "DEBUG=1" environment variable if you want to see why it's slow. PROTIP: Set "DEBUG=2" environment variable if you want to see why it's slow.
### tinygrad supports Stable Diffusion! ### tinygrad supports Stable Diffusion!
@@ -199,6 +181,14 @@ Run `python3 examples/stable_diffusion.py`
"a horse sized cat eating a bagel" "a horse sized cat eating a bagel"
</p> </p>
### tinygrad supports LLaMA
After putting the weights in weights/LLaMA, you can have a chat with Stacy. She lives inside tinygrad.
```bash
python3 examples/llama.py
```
### tinygrad supports GANs ### tinygrad supports GANs
See `examples/mnist_gan.py` See `examples/mnist_gan.py`
@@ -215,18 +205,8 @@ See `examples/yolov3.py`
<img src="https://raw.githubusercontent.com/geohot/tinygrad/master/docs/yolo_by_tinygrad.jpg"> <img src="https://raw.githubusercontent.com/geohot/tinygrad/master/docs/yolo_by_tinygrad.jpg">
</p> </p>
## The promise of small
tinygrad will always be below 1000 lines. If it isn't, we will revert commits until tinygrad becomes smaller.
### Drawing Execution Graph ### Drawing Execution Graph
* Nodes are Tensors
* Black edge is a forward pass
* Blue edge is a backward pass
* Red edge is data the backward pass depends on
* Purple edge is intermediates created in the forward
```bash ```bash
GRAPH=1 python3 test/models/test_mnist.py TestMNIST.test_sgd_onestep GRAPH=1 python3 test/models/test_mnist.py TestMNIST.test_sgd_onestep
# requires dot, outputs /tmp/net.svg # requires dot, outputs /tmp/net.svg