| @@ -428,9 +428,9 @@ namespace Tensorflow.Operations | |||||
| return x; | return x; | ||||
| var x_rank = array_ops.rank(x); | var x_rank = array_ops.rank(x); | ||||
| var con1 = new Tensor[] | |||||
| var con1 = new object[] | |||||
| { | { | ||||
| new Tensor(new int[]{0, 2}), | |||||
| new []{1, 0 }, | |||||
| math_ops.range(2, x_rank) | math_ops.range(2, x_rank) | ||||
| }; | }; | ||||
| var x_t = array_ops.transpose(x, array_ops.concat(con1, 0)); | var x_t = array_ops.transpose(x, array_ops.concat(con1, 0)); | ||||
| @@ -945,12 +945,12 @@ namespace Tensorflow | |||||
| /// <returns></returns> | /// <returns></returns> | ||||
| public static Tensor concat(Tensor[] values, Tensor axis, string name = "concat") | public static Tensor concat(Tensor[] values, Tensor axis, string name = "concat") | ||||
| { | { | ||||
| return gen_array_ops.concat_v2(values, axis, name: name); | |||||
| return tf.Context.ExecuteOp("ConcatV2", name, new ExecuteOpArgs(values, axis)); | |||||
| } | } | ||||
| public static Tensor concat(Tensor[] values, Axis axis, string name = "concat") | |||||
| public static Tensor concat(object[] values, int axis, string name = "concat") | |||||
| { | { | ||||
| return gen_array_ops.concat_v2(values, axis, name: name); | |||||
| return tf.Context.ExecuteOp("ConcatV2", name, new ExecuteOpArgs(values, axis)); | |||||
| } | } | ||||
| /// <summary> | /// <summary> | ||||
| @@ -287,7 +287,7 @@ namespace Tensorflow | |||||
| new[] { math_ops.subtract(rank, 1) }, | new[] { math_ops.subtract(rank, 1) }, | ||||
| new[] { constant_op.constant(1) }); | new[] { constant_op.constant(1) }); | ||||
| var ops = array_ops.concat(new Tensor[] { new Tensor(new int[] {1}), last_dim_size }, 0); | |||||
| var ops = array_ops.concat(new[] { new[] { -1 }, (object)last_dim_size }, 0); | |||||
| var output = array_ops.reshape(logits, ops); | var output = array_ops.reshape(logits, ops); | ||||
| // Set output shape if known. | // Set output shape if known. | ||||