mirror of https://github.com/m-labs/artiq.git
compiler: Fix numpy.full, implement for >1D
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53d64d08a8
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@ -1411,7 +1411,7 @@ class ARTIQIRGenerator(algorithm.Visitor):
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operand = self.visit(node.operand)
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if builtins.is_array(operand.type):
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shape = self.append(ir.GetAttr(operand, "shape"))
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result = self._allocate_new_array(node.type.find()["elt"], shape)
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result, _ = self._allocate_new_array(node.type.find()["elt"], shape)
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func = self._get_array_unaryop("USub", make_sub, node.type, operand.type)
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self._invoke_arrayop(func, [result, operand])
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return result
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@ -1431,7 +1431,7 @@ class ARTIQIRGenerator(algorithm.Visitor):
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if builtins.is_array(node.type):
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result_elt = node.type.find()["elt"]
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shape = self.append(ir.GetAttr(value, "shape"))
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result = self._allocate_new_array(result_elt, shape)
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result, _ = self._allocate_new_array(result_elt, shape)
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func = self._get_array_unaryop(
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"Coerce", lambda v: self.append(ir.Coerce(v, result_elt)),
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node.type, value.type)
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@ -1455,7 +1455,7 @@ class ARTIQIRGenerator(algorithm.Visitor):
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total_length = self._get_total_array_len(shape)
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buffer = self.append(ir.Alloc([total_length], types._TPointer(elt=elt)))
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result_type = builtins.TArray(elt, types.TValue(len(shape.type.elts)))
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return self.append(ir.Alloc([buffer, shape], result_type))
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return self.append(ir.Alloc([buffer, shape], result_type)), total_length
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def _make_array_binop(self, name, result_type, lhs_type, rhs_type, body_gen):
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try:
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@ -1704,7 +1704,7 @@ class ARTIQIRGenerator(algorithm.Visitor):
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elt = final_type["elt"]
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result_dims = final_type["num_dims"].value
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result = self._allocate_new_array(elt, result_shape)
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result, _ = self._allocate_new_array(elt, result_shape)
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func = self._get_matmult(result.type, left.type, right.type)
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self._invoke_arrayop(func, [result, lhs, rhs])
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@ -1745,7 +1745,7 @@ class ARTIQIRGenerator(algorithm.Visitor):
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ir.Constant("operands could not be broadcast together",
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builtins.TStr())))
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result = self._allocate_new_array(node.type.find()["elt"], shape)
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result, _ = self._allocate_new_array(node.type.find()["elt"], shape)
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func = self._get_array_binop(node.op, node.type, lhs.type, rhs.type)
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self._invoke_arrayop(func, [result, lhs, rhs])
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return result
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@ -2223,14 +2223,26 @@ class ARTIQIRGenerator(algorithm.Visitor):
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if len(node.args) == 2 and len(node.keywords) == 0:
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arg0, arg1 = map(self.visit, node.args)
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result = self.append(ir.Alloc([arg0], node.type))
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num_dims = node.type.find()["num_dims"].value
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if types.is_tuple(arg0.type):
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lens = [self.append(ir.GetAttr(arg0, i)) for i in range(num_dims)]
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else:
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assert num_dims == 1
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lens = [arg0]
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shape = self._make_array_shape(lens)
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result, total_len = self._allocate_new_array(node.type.find()["elt"],
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shape)
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def body_gen(index):
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self.append(ir.SetElem(result, index, arg1))
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return self.append(ir.Arith(ast.Add(loc=None), index,
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ir.Constant(1, arg0.type)))
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self._make_loop(ir.Constant(0, self._size_type),
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lambda index: self.append(ir.Compare(ast.Lt(loc=None), index, arg0)),
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body_gen)
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return self.append(
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ir.Arith(ast.Add(loc=None), index,
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ir.Constant(1, self._size_type)))
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self._make_loop(
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ir.Constant(0, self._size_type), lambda index: self.append(
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ir.Compare(ast.Lt(loc=None), index, total_len)), body_gen)
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return result
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else:
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assert False
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@ -2247,7 +2259,7 @@ class ARTIQIRGenerator(algorithm.Visitor):
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dim0 = self.append(ir.GetAttr(arg_shape, 0))
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dim1 = self.append(ir.GetAttr(arg_shape, 1))
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shape = self._make_array_shape([dim1, dim0])
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result = self._allocate_new_array(node.type.find()["elt"], shape)
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result, _ = self._allocate_new_array(node.type.find()["elt"], shape)
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arg_buffer = self.append(ir.GetAttr(arg, "buffer"))
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result_buffer = self.append(ir.GetAttr(result, "buffer"))
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@ -2413,7 +2425,7 @@ class ARTIQIRGenerator(algorithm.Visitor):
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node.arg_exprs)
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shape = self.append(ir.GetAttr(args[0], "shape"))
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result = self._allocate_new_array(node.type.find()["elt"], shape)
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result, _ = self._allocate_new_array(node.type.find()["elt"], shape)
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# TODO: Generate more generically if non-externals are allowed.
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name = node.func.type.find().name
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@ -1103,17 +1103,26 @@ class Inferencer(algorithm.Visitor):
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diagnose(valid_forms())
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elif types.is_builtin(typ, "make_array"):
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valid_forms = lambda: [
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valid_form("numpy.full(count:int32, value:'a) -> numpy.array(elt='a)")
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valid_form("numpy.full(count:int32, value:'a) -> array(elt='a, num_dims=1)"),
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valid_form("numpy.full(shape:(int32,)*'b, value:'a) -> array(elt='a, num_dims='b)"),
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]
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self._unify(node.type, builtins.TArray(),
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node.loc, None)
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if len(node.args) == 2 and len(node.keywords) == 0:
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arg0, arg1 = node.args
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self._unify(arg0.type, builtins.TInt32(),
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arg0.loc, None)
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if types.is_var(arg0.type):
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return # undetermined yet
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elif types.is_tuple(arg0.type):
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num_dims = len(arg0.type.find().elts)
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self._unify(arg0.type, types.TTuple([builtins.TInt32()] * num_dims),
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arg0.loc, None)
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else:
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num_dims = 1
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self._unify(arg0.type, builtins.TInt32(),
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arg0.loc, None)
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self._unify(node.type, builtins.TArray(num_dims=num_dims),
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node.loc, None)
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self._unify(arg1.type, node.type.find()["elt"],
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arg1.loc, None)
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else:
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@ -244,6 +244,10 @@ class _RPCCalls(EnvExperiment):
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def numpy_full(self):
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return numpy.full(10, 20)
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@kernel
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def numpy_full_matrix(self):
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return numpy.full((3, 2), 13)
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@kernel
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def numpy_nan(self):
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return numpy.full(10, numpy.nan)
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@ -277,6 +281,7 @@ class RPCCallsTest(ExperimentCase):
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self.assertEqual(exp.numpy_things(),
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(numpy.int32(10), numpy.int64(20), numpy.array([42,])))
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self.assertTrue((exp.numpy_full() == numpy.full(10, 20)).all())
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self.assertTrue((exp.numpy_full_matrix() == numpy.full((3, 2), 13)).all())
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self.assertTrue(numpy.isnan(exp.numpy_nan()).all())
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exp.builtin()
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exp.async_in_try()
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