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delete revectorize (#9000)

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* delete revectorize

* test vectorized LLVM/CLANG

* idk about that

* was that the segfault?
This commit is contained in:
George Hotz
2025-02-10 18:32:35 +08:00
committed by GitHub
parent fd9f9ec772
commit 0568720a68
8 changed files with 36 additions and 33 deletions
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13
test/test_quantize_onnx.py
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@@ -51,8 +51,8 @@ class TestQuantizeOnnx(unittest.TestCase):
out_file = "/tmp/test_out.onnx"
quantize_static(create_gemm_model("/tmp/test_in.onnx"), out_file,
FakeDataReader(), quant_format=QuantFormat.QDQ, per_channel=False,
activation_type=QuantType.QInt8, weight_type=QuantType.QInt8,
extra_options={"ActivationSymmetric": True})
activation_type=QuantType.QUInt8, weight_type=QuantType.QInt8,
extra_options={"ActivationSymmetric": False})
run_onnx_jit, _ = load_onnx_model(out_file)
with Context(NOOPT=1):
run_onnx_jit(input=Tensor(np.random.uniform(size=(1, N)).astype(np.float32)))
@@ -73,6 +73,15 @@ class TestQuantizeOnnx(unittest.TestCase):
opts = [Opt(op=OptOps.UPCAST, axis=1, arg=128), Opt(op=OptOps.UNROLL, axis=0, arg=4)]
sexec(out, opts)
def test_prequant_gemm_intacc(self):
N = 512
# ugh, it's so broken with those casts. need DONT_REALIZE_EXPAND=1 python3 test/test_quantize_onnx.py TestQuantizeOnnx.test_prequant
X = Tensor(np.random.uniform(0, 255, size=(N,N)).astype(np.uint8))
W = Tensor(np.random.uniform(0, 255, size=(N,N)).astype(np.int8))
out = X.matmul(W)
opts = [Opt(op=OptOps.UPCAST, axis=1, arg=128), Opt(op=OptOps.UNROLL, axis=0, arg=4)]
sexec(out, opts)
def test_prequant_gemv(self):
N = 2048
# ugh, it's so broken with those casts. need DONT_REALIZE_EXPAND=1 python3 test/test_quantize_onnx.py TestQuantizeOnnx.test_prequant