fix: revise np.amin, np.amax and add np.argmintags/v0.110.4-Transformer-Model
@@ -13,6 +13,10 @@ namespace Tensorflow.NumPy | |||||
public static NDArray argmax(NDArray a, Axis? axis = null) | public static NDArray argmax(NDArray a, Axis? axis = null) | ||||
=> new NDArray(math_ops.argmax(a, axis ?? 0)); | => new NDArray(math_ops.argmax(a, axis ?? 0)); | ||||
[AutoNumPy] | |||||
public static NDArray argmin(NDArray a, Axis? axis = null) | |||||
=> new NDArray(math_ops.argmin(a, axis ?? 0)); | |||||
[AutoNumPy] | [AutoNumPy] | ||||
public static NDArray argsort(NDArray a, Axis? axis = null) | public static NDArray argsort(NDArray a, Axis? axis = null) | ||||
=> new NDArray(sort_ops.argsort(a, axis: axis ?? -1)); | => new NDArray(sort_ops.argsort(a, axis: axis ?? -1)); | ||||
@@ -10,10 +10,10 @@ namespace Tensorflow.NumPy | |||||
public partial class np | public partial class np | ||||
{ | { | ||||
[AutoNumPy] | [AutoNumPy] | ||||
public static NDArray amin(NDArray x, int axis = 0) => new NDArray(tf.arg_min(x, axis)); | |||||
public static NDArray amin(NDArray x, int axis = 0) => new NDArray(tf.min(x, axis)); | |||||
[AutoNumPy] | [AutoNumPy] | ||||
public static NDArray amax(NDArray x, int axis = 0) => new NDArray(tf.math.argmax(x, axis)); | |||||
public static NDArray amax(NDArray x, int axis = 0) => new NDArray(tf.max(x, axis)); | |||||
[AutoNumPy] | [AutoNumPy] | ||||
public static NDArray average(NDArray a, int axis = -1, NDArray? weights = null, bool returned = false) | public static NDArray average(NDArray a, int axis = -1, NDArray? weights = null, bool returned = false) | ||||
@@ -77,6 +77,9 @@ namespace Tensorflow | |||||
public static Tensor argmax(Tensor input, Axis dimension, TF_DataType output_type = TF_DataType.TF_INT64, string name = null) | public static Tensor argmax(Tensor input, Axis dimension, TF_DataType output_type = TF_DataType.TF_INT64, string name = null) | ||||
=> gen_math_ops.arg_max(input, dimension, output_type: output_type, name: name); | => gen_math_ops.arg_max(input, dimension, output_type: output_type, name: name); | ||||
public static Tensor argmin(Tensor input, Axis dimension, TF_DataType output_type = TF_DataType.TF_INT64, string name = null) | |||||
=> gen_math_ops.arg_min(input, dimension, output_type: output_type, name: name); | |||||
public static Tensor round(Tensor x, string name = null) | public static Tensor round(Tensor x, string name = null) | ||||
{ | { | ||||
x = ops.convert_to_tensor(x, name: "x"); | x = ops.convert_to_tensor(x, name: "x"); | ||||