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Add PR # to changelog
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‎docs/changelog.md

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@@ -21,7 +21,7 @@ _This project uses semantic versioning. Before 1.0.0, this means that every brea
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- Upgraded `egg-smol` dependency ([changes](https://github.com/saulshanabrook/egg-smol/compare/353c4387640019bd2066991ee0488dc6d5c54168...2ac80cb1162c61baef295d8e6d00351bfe84883f))
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- Add support for functions which mutates their args, like `__setitem__` [#35](https://github.com/metadsl/egglog-python/pull/35)
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- Makes conversions transitive
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- Makes conversions transitive [#38](https://github.com/metadsl/egglog-python/pull/38)
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## 0.5.1 (2023-07-18)
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‎docs/tutorials/array-api.ipynb

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@@ -66,7 +66,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -84,7 +84,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
104+
"isdtype(DType.float32, IsDtypeKind.string(\"integral\"))\n",
105+
" -> FALSE\n",
106+
" -> FALSE\n",
107+
"DType.float64 == NDArray.var(\"X\").dtype\n",
108+
" -> DType.float64 == NDArray.var(\"X\").dtype\n",
109+
" -> TRUE\n",
110+
"asarray(NDArray.var(\"X\")).ndim == Int(0)\n",
111+
" -> NDArray.var(\"X\").ndim == Int(0)\n",
112+
" -> FALSE\n",
113+
"asarray(NDArray.var(\"X\")).ndim == Int(1)\n",
114+
" -> NDArray.var(\"X\").ndim == Int(1)\n",
115+
" -> FALSE\n",
116+
"asarray(NDArray.var(\"X\")).ndim >= Int(3)\n",
117+
" -> NDArray.var(\"X\").ndim >= Int(3)\n",
118+
" -> FALSE\n",
119+
"asarray(asarray(NDArray.var(\"X\"))).dtype == DType.object\n",
120+
" -> NDArray.var(\"X\").dtype == DType.object\n",
121+
" -> FALSE\n",
122+
"isdtype(asarray(asarray(NDArray.var(\"X\"))).dtype, (IsDtypeKind.string(\"real floating\") | (IsDtypeKind.string(\"complex floating\") | IsDtypeKind.NULL)))\n",
123+
" -> isdtype(NDArray.var(\"X\").dtype, (IsDtypeKind.string(\"real floating\") | IsDtypeKind.string(\"complex floating\")))\n",
124+
" -> TRUE\n",
125+
"isfinite(sum(asarray(asarray(NDArray.var(\"X\"))))).to_bool()\n",
126+
" -> isfinite(sum(NDArray.var(\"X\"))).to_bool()\n",
127+
" -> TRUE\n",
128+
"asarray(NDArray.var(\"X\")).shape.length()\n",
129+
" -> NDArray.var(\"X\").ndim\n",
130+
" -> Int(2)\n",
131+
"asarray(NDArray.var(\"X\")).shape[Int(0)] < Int(2)\n",
132+
" -> NDArray.var(\"X\").shape[Int(0)] < Int(2)\n",
133+
" -> FALSE\n",
134+
"asarray(NDArray.var(\"X\")).ndim == Int(2)\n",
135+
" -> NDArray.var(\"X\").ndim == Int(2)\n",
136+
" -> TRUE\n",
137+
"asarray(NDArray.var(\"X\")).shape[Int(1)] < Int(1)\n",
138+
" -> NDArray.var(\"X\").shape[Int(1)] < Int(1)\n",
139+
" -> FALSE\n",
140+
"asarray(NDArray.var(\"y\")).ndim >= Int(3)\n",
141+
" -> NDArray.var(\"y\").ndim >= Int(3)\n",
142+
" -> FALSE\n",
143+
"asarray(NDArray.var(\"y\")).ndim == Int(2)\n",
144+
" -> NDArray.var(\"y\").ndim == Int(2)\n",
145+
" -> FALSE\n",
146+
"asarray(NDArray.var(\"y\")).shape.length()\n",
147+
" -> NDArray.var(\"y\").ndim\n",
148+
" -> Int(1)\n",
149+
"asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).dtype == DType.object\n",
150+
" -> NDArray.var(\"y\").dtype == DType.object\n",
151+
" -> FALSE\n",
152+
"isdtype(\n",
153+
" asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).dtype,\n",
154+
" (IsDtypeKind.string(\"real floating\") | (IsDtypeKind.string(\"complex floating\") | IsDtypeKind.NULL)),\n",
155+
")\n",
156+
" -> isdtype(NDArray.var(\"y\").dtype, (IsDtypeKind.string(\"real floating\") | IsDtypeKind.string(\"complex floating\")))\n",
157+
" -> FALSE\n",
158+
"asarray(NDArray.var(\"X\")).shape.length()\n",
159+
" -> NDArray.var(\"X\").ndim\n",
160+
" -> Int(2)\n",
161+
"asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))).shape.length()\n",
162+
" -> Int(1)\n",
163+
" -> Int(1)\n",
164+
"asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))).shape[Int(0)] < asarray(NDArray.var(\"X\")).shape[Int(0)]\n",
165+
" -> NDArray.var(\"y\").size < NDArray.var(\"X\").shape[Int(0)]\n",
166+
" -> FALSE\n",
167+
"asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))).shape[Int(0)] > asarray(NDArray.var(\"X\")).shape[Int(0)]\n",
168+
" -> NDArray.var(\"y\").size > NDArray.var(\"X\").shape[Int(0)]\n",
169+
" -> FALSE\n",
170+
"asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))).shape[Int(0)] == asarray(NDArray.var(\"X\")).shape[Int(0)]\n",
171+
" -> NDArray.var(\"y\").size == NDArray.var(\"X\").shape[Int(0)]\n",
172+
" -> TRUE\n",
173+
"asarray(NDArray.var(\"X\")).shape.length()\n",
174+
" -> NDArray.var(\"X\").ndim\n",
175+
" -> Int(2)\n",
176+
"asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).ndim == Int(2)\n",
177+
" -> FALSE\n",
178+
" -> FALSE\n",
179+
"asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).ndim == Int(1)\n",
180+
" -> TRUE\n",
181+
" -> TRUE\n",
182+
"asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).shape.length()\n",
183+
" -> Int(1)\n",
184+
" -> Int(1)\n",
185+
"asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).shape[Int(0)] == Int(0)\n",
186+
" -> NDArray.var(\"y\").size == Int(0)\n",
187+
" -> FALSE\n",
188+
"asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).dtype == DType.object\n",
189+
" -> NDArray.var(\"y\").dtype == DType.object\n",
190+
" -> FALSE\n",
191+
"asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).ndim == Int(2)\n",
192+
" -> FALSE\n",
193+
" -> FALSE\n",
194+
"isdtype(asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).dtype, IsDtypeKind.string(\"real floating\"))\n",
195+
" -> isdtype(NDArray.var(\"y\").dtype, IsDtypeKind.string(\"real floating\"))\n",
196+
" -> FALSE\n",
197+
"unique_values(asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))))).shape[Int(0)] > Int(2)\n",
198+
" -> unique_values(reshape(NDArray.var(\"y\"), TupleInt(Int(-1)))).shape[Int(0)] > Int(2)\n",
199+
" -> TRUE\n",
200+
"asarray(NDArray.var(\"X\")).shape.length()\n",
201+
" -> NDArray.var(\"X\").ndim\n",
202+
" -> Int(2)\n",
203+
"asarray(NDArray.var(\"X\")).shape[Int(0)] == unique_values(\n",
204+
" concat((TupleNDArray(unique_values(asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))))) + TupleNDArray.EMPTY))\n",
205+
").shape[Int(0)]\n",
206+
" -> NDArray.var(\"X\").shape[Int(0)] == unique_values(reshape(NDArray.var(\"y\"), TupleInt(Int(-1)))).shape[Int(0)]\n",
207+
" -> FALSE\n",
208+
"unique_counts(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).length()\n",
209+
" -> Int(2)\n",
210+
" -> Int(2)\n",
211+
"asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))).shape[Int(0)]\n",
212+
" -> NDArray.var(\"y\").size\n",
213+
" -> Int(150)\n",
214+
"any(\n",
215+
" (\n",
216+
" (\n",
217+
" astype(unique_counts(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))))[Int(1)], asarray(NDArray.var(\"X\")).dtype)\n",
218+
" / NDArray.scalar_float(Float(150.0))\n",
219+
" )\n",
220+
" < NDArray.scalar_int(Int(0))\n",
221+
" )\n",
222+
").to_bool()\n",
223+
" -> FALSE\n",
224+
" -> FALSE\n",
225+
"(\n",
226+
" abs(\n",
227+
" (\n",
228+
" sum(\n",
229+
" (\n",
230+
" astype(unique_counts(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))))[Int(1)], asarray(NDArray.var(\"X\")).dtype)\n",
231+
" / NDArray.scalar_float(Float(150.0))\n",
232+
" )\n",
233+
" )\n",
234+
" - NDArray.scalar_float(Float(1.0))\n",
235+
" )\n",
236+
" )\n",
237+
" > NDArray.scalar_float(Float(1e-05))\n",
238+
").to_bool()\n",
239+
" -> (\n",
240+
" abs(\n",
241+
" (\n",
242+
" (astype(NDArray.scalar_int(reshape(NDArray.var(\"y\"), TupleInt(Int(-1))).size), NDArray.var(\"X\").dtype) / NDArray.scalar_float(Float(150.0)))\n",
243+
" - NDArray.scalar_float(Float(1.0))\n",
244+
" )\n",
245+
" )\n",
246+
" > NDArray.scalar_float(Float(1e-05))\n",
247+
").to_bool()\n",
248+
" -> FALSE\n",
249+
"asarray(NDArray.var(\"X\")).shape[Int(1)] < (\n",
250+
" unique_values(concat((TupleNDArray(unique_values(asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))))) + TupleNDArray.EMPTY))).shape[\n",
251+
" Int(0)\n",
252+
" ]\n",
253+
" - Int(1)\n",
254+
")\n",
255+
" -> NDArray.var(\"X\").shape[Int(1)] < (unique_values(reshape(NDArray.var(\"y\"), TupleInt(Int(-1)))).shape[Int(0)] - Int(1))\n",
256+
" -> FALSE\n",
257+
"(\n",
258+
" unique_values(concat((TupleNDArray(unique_values(asarray(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))))) + TupleNDArray.EMPTY))).shape[\n",
259+
" Int(0)\n",
260+
" ]\n",
261+
" - Int(1)\n",
262+
") < Int(2)\n",
263+
" -> (unique_values(reshape(NDArray.var(\"y\"), TupleInt(Int(-1)))).shape[Int(0)] - Int(1)) < Int(2)\n",
264+
" -> FALSE\n",
265+
"asarray(NDArray.var(\"X\")).shape.length()\n",
266+
" -> NDArray.var(\"X\").ndim\n",
267+
" -> Int(2)\n",
268+
"unique_inverse(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY)))).length()\n",
269+
" -> Int(2)\n",
270+
" -> Int(2)\n",
271+
"unique_inverse(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))))[Int(0)].shape[Int(0)]\n",
272+
"unique_inverse(asarray(reshape(asarray(NDArray.var(\"y\")), (TupleInt(Int(-1)) + TupleInt.EMPTY))))[Int(0)].shape[Int(0)]\n",
273+
" -> unique_values(reshape(NDArray.var(\"y\"), TupleInt(Int(-1)))).shape[Int(0)]\n",
274+
" -> Int(3)\n"
275+
]
276+
},
277+
{
278+
"ename": "TypeError",
279+
"evalue": "NDArray has no method __iter__",
280+
"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
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"File \u001b[0;32m~/p/egg-smol-python/python/egglog/runtime.py:452\u001b[0m, in \u001b[0;36m_preserved_method\u001b[0;34m(self, __name)\u001b[0m\n\u001b[1;32m 451\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 452\u001b[0m method \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__egg_decls__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_class_decl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__egg_typed_expr__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpreserved_methods\u001b[49m\u001b[43m[\u001b[49m\u001b[43m__name\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 453\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n",
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"\u001b[0;31mKeyError\u001b[0m: '__iter__'",
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"\nDuring handling of the above exception, another exception occurred:\n",
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"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[4], line 21\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;66;03m# Add values for the constants\u001b[39;00m\n\u001b[1;32m 8\u001b[0m egraph\u001b[38;5;241m.\u001b[39mregister(\n\u001b[1;32m 9\u001b[0m rewrite(X_arr\u001b[38;5;241m.\u001b[39mdtype, runtime_ruleset)\u001b[38;5;241m.\u001b[39mto(convert(X\u001b[38;5;241m.\u001b[39mdtype, DType)),\n\u001b[1;32m 10\u001b[0m rewrite(y_arr\u001b[38;5;241m.\u001b[39mdtype, runtime_ruleset)\u001b[38;5;241m.\u001b[39mto(convert(y\u001b[38;5;241m.\u001b[39mdtype, DType)),\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 17\u001b[0m rewrite(unique_values(y_arr)\u001b[38;5;241m.\u001b[39mshape)\u001b[38;5;241m.\u001b[39mto(TupleInt(Int(\u001b[38;5;241m3\u001b[39m))),\n\u001b[1;32m 18\u001b[0m )\n\u001b[0;32m---> 21\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_arr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_arr\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 23\u001b[0m \u001b[38;5;66;03m# X_obj, y_obj = egraph.save_object(X), egraph.save_object(y)\u001b[39;00m\n\u001b[1;32m 24\u001b[0m \n\u001b[1;32m 25\u001b[0m \u001b[38;5;66;03m# X_arr = NDArray(X_obj)\u001b[39;00m\n\u001b[1;32m 26\u001b[0m \u001b[38;5;66;03m# y_arr = NDArray(y_obj)\u001b[39;00m\n",
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"Cell \u001b[0;32mIn[1], line 15\u001b[0m, in \u001b[0;36mfit\u001b[0;34m(X, y)\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m config_context(array_api_dispatch\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m 14\u001b[0m lda \u001b[38;5;241m=\u001b[39m LinearDiscriminantAnalysis(n_components\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m---> 15\u001b[0m X_r2 \u001b[38;5;241m=\u001b[39m \u001b[43mlda\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mtransform(X)\n\u001b[1;32m 16\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m X_r2\n\u001b[1;32m 18\u001b[0m target_names \u001b[38;5;241m=\u001b[39m iris\u001b[38;5;241m.\u001b[39mtarget_names\n",
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"File \u001b[0;32m/usr/local/Caskroom/miniconda/base/envs/egg-smol-python/lib/python3.10/site-packages/sklearn/base.py:1151\u001b[0m, in \u001b[0;36m_fit_context.<locals>.decorator.<locals>.wrapper\u001b[0;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1144\u001b[0m estimator\u001b[38;5;241m.\u001b[39m_validate_params()\n\u001b[1;32m 1146\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[1;32m 1147\u001b[0m skip_parameter_validation\u001b[38;5;241m=\u001b[39m(\n\u001b[1;32m 1148\u001b[0m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[1;32m 1149\u001b[0m )\n\u001b[1;32m 1150\u001b[0m ):\n\u001b[0;32m-> 1151\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfit_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
291+
"File \u001b[0;32m/usr/local/Caskroom/miniconda/base/envs/egg-smol-python/lib/python3.10/site-packages/sklearn/discriminant_analysis.py:629\u001b[0m, in \u001b[0;36mLinearDiscriminantAnalysis.fit\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 623\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcovariance_estimator \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 624\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 625\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcovariance estimator \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 626\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mis not supported \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 627\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwith svd solver. Try another solver\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 628\u001b[0m )\n\u001b[0;32m--> 629\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_solve_svd\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 630\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msolver \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlsqr\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 631\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_solve_lstsq(\n\u001b[1;32m 632\u001b[0m X,\n\u001b[1;32m 633\u001b[0m y,\n\u001b[1;32m 634\u001b[0m shrinkage\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mshrinkage,\n\u001b[1;32m 635\u001b[0m covariance_estimator\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcovariance_estimator,\n\u001b[1;32m 636\u001b[0m )\n",
292+
"File \u001b[0;32m/usr/local/Caskroom/miniconda/base/envs/egg-smol-python/lib/python3.10/site-packages/sklearn/discriminant_analysis.py:506\u001b[0m, in \u001b[0;36mLinearDiscriminantAnalysis._solve_svd\u001b[0;34m(self, X, y)\u001b[0m\n\u001b[1;32m 503\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcovariance_ \u001b[38;5;241m=\u001b[39m _class_cov(X, y, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpriors_)\n\u001b[1;32m 505\u001b[0m Xc \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m--> 506\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m idx, group \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclasses_\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 507\u001b[0m Xg \u001b[38;5;241m=\u001b[39m X[y \u001b[38;5;241m==\u001b[39m group]\n\u001b[1;32m 508\u001b[0m Xc\u001b[38;5;241m.\u001b[39mappend(Xg \u001b[38;5;241m-\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmeans_[idx, :])\n",
293+
"File \u001b[0;32m~/p/egg-smol-python/python/egglog/runtime.py:454\u001b[0m, in \u001b[0;36m_preserved_method\u001b[0;34m(self, __name)\u001b[0m\n\u001b[1;32m 452\u001b[0m method \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__egg_decls__\u001b[38;5;241m.\u001b[39mget_class_decl(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__egg_typed_expr__\u001b[38;5;241m.\u001b[39mtp\u001b[38;5;241m.\u001b[39mname)\u001b[38;5;241m.\u001b[39mpreserved_methods[__name]\n\u001b[1;32m 453\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n\u001b[0;32m--> 454\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m__egg_typed_expr__\u001b[38;5;241m.\u001b[39mtp\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m has no method \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m__name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 455\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m method(\u001b[38;5;28mself\u001b[39m)\n",
294+
"\u001b[0;31mTypeError\u001b[0m: NDArray has no method __iter__"
295+
]
296+
}
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],
100298
"source": [
101299
"from egglog.exp.array_api import *\n",
102300
"\n",

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