mirror of https://github.com/Nonannet/copapy.git
code style fixed
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0fd292ecfa
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f63e09fb99
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@ -79,7 +79,7 @@ def get_all_dag_edges_between(roots: Iterable[Node], leaves: Iterable[Node]) ->
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# Walk the DAG in reverse direction starting from given leaves to given roots
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emitted_edges: set[tuple[Node, Node]] = set()
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node_list = [n for n in leaves]
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node_list = list(leaves)
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while(node_list):
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child_node = node_list.pop()
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if child_node in parent_lookup:
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@ -104,13 +104,13 @@ def get_all_dag_edges(nodes: Iterable[Node]) -> Generator[tuple[Node, Node], Non
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"""
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emitted_edges: set[tuple[Node, Node]] = set()
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used_nets: dict[Net, Net] = {}
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node_list: list[Node] = [n for n in nodes]
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node_list: list[Node] = list(nodes)
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while(node_list):
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node = node_list.pop()
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for net in node.args:
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# In case there is already net with equivalent value use this
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# In case there is already net with equivalent value use this
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if net in used_nets:
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net = used_nets[net]
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else:
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@ -362,7 +362,7 @@ class stencil_database():
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patch_value = symbol_address + pr.fields['r_addend']
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symbol_type = symbol_type + 0x06 # PATCH_OBJECT_ARM32_ABS_THM
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#print(f" *> {pr.type} {patch_value=} {symbol_address=}, {function_offset=}, {pr.fields['r_addend']=}")
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elif pr.type == 'R_ARM_THM_MOVT_ABS':
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# (S + A) & 0xFFFF0000
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mask = 0xFFFF0000
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@ -1,4 +1,4 @@
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def coparun(context: int, data: bytes) -> int: ...
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def read_data_mem(context: int, rel_addr: int, length: int) -> bytes: ...
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def create_target() -> int: ...
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def clear_target(context: int) -> None: ...
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def clear_target(context: int) -> None: ...
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@ -303,7 +303,7 @@ if __name__ == "__main__":
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code += get_custom_stencil('abs_int(int arg1)', 'result_int(__builtin_abs(arg1));')
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for t in types:
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code += get_custom_stencil(f"sign_{t}({t} arg1)", f"result_int((arg1 > 0) - (arg1 < 0));")
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code += get_custom_stencil(f"sign_{t}({t} arg1)", "result_int((arg1 > 0) - (arg1 < 0));")
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fnames = ['atan2', 'pow']
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for fn, t1, t2 in permutate(fnames, types, types):
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@ -7,8 +7,6 @@ import sys
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import numpy as np
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from numpy.core._multiarray_umath import __cpu_features__
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from copapy._matrices import diagonal
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CPU_SIMD_FEATURES = "SSE SSE2 SSE3 SSSE3 SSE41 SSE42 AVX AVX2 AVX512F FMA3"
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@ -217,7 +215,7 @@ def save_svg_with_theme_styles(pyplot_obj, path):
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# --- Step 1: Capture SVG to memory ---
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buf = io.StringIO()
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# pyplot_obj can be a module (plt) or a Figure instance
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if hasattr(pyplot_obj, "gcf"):
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fig = pyplot_obj.gcf()
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@ -70,4 +70,4 @@ def test_dag_reduction():
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if __name__ == "__main__":
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test_get_dag_stats()
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test_dag_reduction()
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test_dag_reduction()
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@ -181,4 +181,4 @@ qemu-arm -d in_asm,exec -D qemu_trace.log \
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-global driver=pl011.audiomaddr,property=addr,value=0xff7ec000 \
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-global driver=pl011.audiomaddr,property=size,value=0x100000 \
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your_binary
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"""
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"""
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@ -18,7 +18,7 @@ def forward_kinematics(theta1: cp.value[float] | float, theta2: cp.value[float]
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return joint, end_effector
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def test_two_arms():
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def test_two_arms():
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target_vec = cp.vector(target)
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theta = cp.vector([cp.value(0.0), cp.value(0.0)])
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@ -47,4 +47,4 @@ def test_two_arms():
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if __name__ == '__main__':
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test_two_arms()
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test_two_arms()
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@ -68,7 +68,7 @@ def test_tensor_basic():
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assert result_2d_1d.shape == (2, 3)
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assert result_2d_1d[0, 0] == 11.0
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assert result_2d_1d[1, 2] == 36.0
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# 3D tensor + 2D tensor
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t3d = cp.tensor([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]])
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t2d_broadcast = cp.tensor([[100.0, 200.0], [300.0, 400.0]])
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@ -77,7 +77,7 @@ def test_tensor_basic():
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assert result_3d_2d.shape == (2, 2, 2)
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assert result_3d_2d[0, 0, 0] == 101.0
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assert result_3d_2d[1, 1, 1] == 408.0
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# 3D tensor + 1D tensor
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t1d_broadcast = cp.tensor([1.0, 2.0])
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result_3d_1d = t3d + t1d_broadcast
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@ -106,7 +106,7 @@ def test_tensor_basic():
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assert c2d.shape == (2, 2)
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assert c2d[0, 0] == 2.0
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assert c2d[1, 1] == 20.0
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# 3D - 2D
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t3d_sub = cp.tensor([[[10.0, 20.0], [30.0, 40.0]], [[50.0, 60.0], [70.0, 80.0]]])
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t2d_sub = cp.tensor([[1.0, 2.0], [3.0, 4.0]])
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@ -173,7 +173,7 @@ def test_tensor_basic():
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print("Test 10b: Sum with multiple axes and keepdims")
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t3d = cp.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
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print(f"Original 3D tensor: shape={t3d.shape}")
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# Sum along multiple axes
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sum_axes_0_2 = t3d.sum(axis=(0, 2))
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print(f"Sum along axes (0, 2): shape={sum_axes_0_2.shape}")
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@ -181,17 +181,17 @@ def test_tensor_basic():
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assert sum_axes_0_2[0] == 1 + 2 + 5 + 6 # Elements from [0,:,*] and [1,:,*]
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assert sum_axes_0_2[1] == 3 + 4 + 7 + 8
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print(f"Values: {[sum_axes_0_2[i] for i in range(len(sum_axes_0_2))]}")
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# Sum with keepdims
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sum_keepdims = t3d.sum(axis=1, keepdims=True)
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print(f"Sum along axis 1 with keepdims: shape={sum_keepdims.shape}")
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assert sum_keepdims.shape == (2, 1, 2), f"Expected (2, 1, 2), got {sum_keepdims.shape}"
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# Sum multiple axes with keepdims
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sum_multi_keepdims = t3d.sum(axis=(0, 2), keepdims=True)
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print(f"Sum along axes (0, 2) with keepdims: shape={sum_multi_keepdims.shape}")
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assert sum_multi_keepdims.shape == (1, 2, 1), f"Expected (1, 2, 1), got {sum_multi_keepdims.shape}"
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# Sum all axes with keepdims
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sum_all_keepdims = t3d.sum(keepdims=True)
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print(f"Sum all with keepdims: shape={sum_all_keepdims.shape}")
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@ -13,4 +13,4 @@ dw, _ = compile_to_dag([Store(result)], sdb)
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# Instruct runner to dump patched code to a file:
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dw.write_com(Command.DUMP_CODE)
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dw.to_file('build/runner/test.copapy')
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dw.to_file('build/runner/test.copapy')
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