[API Compatibility] instance_norm/to_empty/linalg.det/gumbel_softmax/vstack/addcdiv/batch_norm/set_default_device/set_grad_enabled/new_tensor/_Loss/_pair/histc/hstack/true_divide_/linalg.eigh/Tensor.H/ELU/relu6/clamp_max/qr/logdet/linalg.cholesky/elu/tensordot/prelu/expand_copy/linalg.qr/clamp_

paddle/fluid/pybind/arg_pre_process.cc

@@ -563,6 +563,84 @@ void PixelShufflePreProcess(std::string* data_format) {
   }
 }
 
+// Eigh input validation for dygraph
+void EighPreProcess(Tensor* x, std::string* UPLO) {
+  auto x_shape = x->dims();
+  int64_t rank = x_shape.size();
+  PADDLE_ENFORCE_GE(rank,
+                    2,
+                    phi::errors::InvalidArgument(
+                        "Input(input) only support >=2 tensor, but received "
+                        "length of Input(input) is %ld.",
+                        rank));
+  PADDLE_ENFORCE_EQ(x_shape[rank - 1],
+                    x_shape[rank - 2],
+                    phi::errors::InvalidArgument(
+                        "The input matrix must be batches of square matrices. "
+                        "But received x's dimension: [%s]",
+                        x_shape));
+  PADDLE_ENFORCE(
+      *UPLO == "L" || *UPLO == "U",
+      phi::errors::InvalidArgument(
+          "UPLO must be L or U. But received UPLO is: %s", UPLO->c_str()));
+}
+
+// Eigh input validation for static graph
+void EighPreProcess(Value* x, std::string* UPLO) {
+  auto x_shape = pir::GetShapeFromValue(*x);
+  int64_t rank = x_shape.size();
+  PADDLE_ENFORCE_GE(rank,
+                    2,
+                    phi::errors::InvalidArgument(
+                        "Input(input) only support >=2 tensor, but received "
+                        "length of Input(input) is %ld.",
+                        rank));
+  PADDLE_ENFORCE_EQ(x_shape[rank - 1],
+                    x_shape[rank - 2],
+                    phi::errors::InvalidArgument(
+                        "The input matrix must be batches of square matrices. "
+                        "But received x's dimension."));
+  PADDLE_ENFORCE(
+      *UPLO == "L" || *UPLO == "U",
+      phi::errors::InvalidArgument(
+          "UPLO must be L or U. But received UPLO is: %s", UPLO->c_str()));
+}
+
+// Cholesky input validation for dygraph
+void CholeskyPreProcess(Tensor* x, bool* upper) {
+  auto x_shape = x->dims();
+  int64_t rank = x_shape.size();
+  PADDLE_ENFORCE_GE(
+      rank,
+      2,
+      phi::errors::InvalidArgument("Shape must have at least 2 dimensions. "
+                                   "But received x's dimension: %ld.",
+                                   rank));
+  PADDLE_ENFORCE_EQ(
+      x_shape[rank - 1],
+      x_shape[rank - 2],
+      phi::errors::InvalidArgument("The last two dimensions must be equal. "
+                                   "But received x's dimension: [%s]",
+                                   x_shape));
+}
+
+// Cholesky input validation for static graph
+void CholeskyPreProcess(Value* x, bool* upper) {
+  auto x_shape = pir::GetShapeFromValue(*x);
+  int64_t rank = x_shape.size();
+  PADDLE_ENFORCE_GE(
+      rank,
+      2,
+      phi::errors::InvalidArgument("Shape must have at least 2 dimensions. "
+                                   "But received x's dimension: %ld.",
+                                   rank));
+  PADDLE_ENFORCE_EQ(
+      x_shape[rank - 1],
+      x_shape[rank - 2],
+      phi::errors::InvalidArgument("The last two dimensions must be equal. "
+                                   "But received x's dimension."));
+}
+
 // Renorm preprocessing: handle negative axis
 void NegativeAxisPreProcess(Tensor* x, int* axis) {
   int rank = x->dims().size();

paddle/fluid/pybind/arg_pre_process.h

@@ -82,6 +82,15 @@ void NegativeAxisPreProcess(Value* x, int* axis);
 
 void PixelShufflePreProcess(std::string* data_format);
 
+// Eigh input validation: check shape >= 2D, last two dims equal, UPLO is 'L' or
+// 'U'
+void EighPreProcess(Tensor* x, std::string* UPLO);
+void EighPreProcess(Value* x, std::string* UPLO);
+
+// Cholesky input validation: check shape >= 2D, last two dims equal
+void CholeskyPreProcess(Tensor* x, bool* upper);
+void CholeskyPreProcess(Value* x, bool* upper);
+
 // Inplace API broadcast validation for dygraph
 void InplaceShapePreProcess(Tensor* x, Tensor* y);
 

paddle/phi/ops/yaml/python_api_info.yaml

@@ -287,6 +287,13 @@
   args_alias :
     use_default_mapping : True
 
+- op : cholesky
+  name : [paddle.cholesky, paddle.linalg.cholesky, paddle.Tensor.cholesky]
+  args_alias :
+    use_default_mapping : True
+  pre_process :
+    func : CholeskyPreProcess(x, upper)
+
 - op : conj
   name: [paddle.conj, paddle.Tensor.conj]
   args_alias :
@@ -325,12 +332,24 @@
     axis1 : [dim1]
     axis2 : [dim2]
 
+- op : det
+  name : [paddle.det, paddle.linalg.det, paddle.Tensor.det]
+  args_alias :
+    x : [input, A]
+
 - op : dot
   name : [paddle.dot, paddle.Tensor.dot]
   args_alias :
     x : [input]
     y : [tensor]
 
+- op : eigh
+  name : [paddle.linalg.eigh, paddle.Tensor.eigh]
+  args_alias :
+    use_default_mapping : True
+  pre_process :
+    func : EighPreProcess(x, UPLO)
+
 - op : erf
   name : [paddle.erf, paddle.Tensor.erf]
   args_alias :

python/paddle/__init__.py

@@ -515,6 +515,7 @@ def new_init(self, *args, **kwargs):
     dstack,
     expand,
     expand_as,
+    expand_copy,
     flatten,
     flatten_,
     flip,
@@ -623,6 +624,7 @@ def new_init(self, *args, **kwargs):
     cartesian_prod,
     ceil,
     clip,
+    clip_,
     combinations,
     conj,
     copysign,
@@ -768,6 +770,7 @@ def new_init(self, *args, **kwargs):
     trace,
     trapezoid,
     true_divide,
+    true_divide_,
     trunc,
     trunc_,
     vander,
@@ -1055,6 +1058,7 @@ def __dir__(self):
 concatenate = concat
 take_along_dim = take_along_axis
 clamp = clip
+clamp_ = clip_
 ger = outer
 div = divide
 div_ = divide_
@@ -1080,6 +1084,67 @@ def __dir__(self):
 negative_ = neg_
 pinverse = pinv
 
+
+def clamp_max(x, max=None, *, out=None):
+    """
+    Clamps all elements in input into the range [min=None, max].
+
+    This is a wrapper around ``paddle.clip`` that only sets the upper bound.
+
+    Args:
+        x (Tensor): The input Tensor. Alias: input.
+        max (float|Tensor): The upper bound.
+        out (Tensor|None, optional): The output Tensor. Default: None.
+
+    Returns:
+        Tensor: The clamped Tensor.
+    """
+    return clip(x, min=None, max=max, name=None, out=out)
+
+
+def qr(input, some=True, *, out=None):
+    """
+    Computes the QR decomposition of one or a batch of matrices.
+
+    This is a wrapper around ``paddle.linalg.qr`` with PyTorch-compatible
+    ``some`` parameter.
+
+    Args:
+        input (Tensor): The input tensor of shape ``[*, M, N]``.
+        some (bool, optional): Controls the shape of Q and R. If ``True`` (default),
+            returns reduced QR (Q: ``[*, M, K]``, R: ``[*, K, N]`` where ``K = min(M, N)``).
+            If ``False``, returns complete QR (Q: ``[*, M, M]``, R: ``[*, M, N]``).
+        out (tuple[Tensor, Tensor]|None, optional): The output tuple of (Q, R). Default: None.
+
+    Returns:
+        tuple[Tensor, Tensor]: A tuple (Q, R).
+    """
+    return linalg.qr(
+        input,
+        mode='reduced' if some else 'complete',
+        out=out,
+    )
+
+
+def logdet(x, name=None):
+    """
+    Computes the natural logarithm of the determinant of a square matrix or
+    batches of square matrices.
+
+    For matrices with negative determinant, returns ``nan``.
+    For matrices with zero determinant, returns ``-inf``.
+
+    Args:
+        x (Tensor): The input tensor of shape ``[*, n, n]`` where ``*``
+            is zero or more batch dimensions.
+        name (str|None, optional): Name for the operation. Default: None.
+
+    Returns:
+        Tensor: The log-determinant of ``x``, with shape ``[*]``.
+    """
+    return linalg.det(x).log()
+
+
 __all__ = [
     'block_diag',
     'gt',
@@ -1215,7 +1280,10 @@ def __dir__(self):
     'less_',
     'kron',
     'clip',
+    'clip_',
     'clamp',
+    'clamp_',
+    'clamp_max',
     'Tensor',
     'FloatTensor',
     'DoubleTensor',
@@ -1329,6 +1397,7 @@ def __dir__(self):
     'CPUPlace',
     'matmul',
     'pinverse',
+    'qr',
     'seed',
     'acos',
     'acos_',
@@ -1377,6 +1446,7 @@ def __dir__(self):
     'sub',
     'sub_',
     'true_divide',
+    'true_divide_',
     'gammaln',
     'gammaln_',
     'ceil',
@@ -1457,6 +1527,7 @@ def __dir__(self):
     'set_default_tensor_type',
     'disable_signal_handler',
     'expand_as',
+    'expand_copy',
     'stack',
     'hstack',
     'vstack',
@@ -1488,6 +1559,7 @@ def __dir__(self):
     'cosh',
     'log',
     'log_',
+    'logdet',
     'log2',
     'log2_',
     'log10',