- paddle.fluid.layers.control_flow. array_length ( array )
This OP is used to get the length of the input array api_fluid_LoDTensorArray . It can be used together with api_fluid_layers_array_read , api_fluid_layers_array_write , api_fluid_layers_While OP to traverse, read and write LoDTensorArray.
array (LoDTensorArray) – The input array that will be used to compute the length.
1-D Tensor with shape , which is the length of array. Datatype: int64.
- Return type
import paddle.fluid as fluid tmp = fluid.layers.zeros(shape=, dtype='int32') i = fluid.layers.fill_constant(shape=, dtype='int64', value=10) # tmp is 1-D Tensor with shape . We write tmp into arr on subscript 10, # then the length of arr becomes 11. arr = fluid.layers.array_write(tmp, i=i) # return the length of arr arr_len = fluid.layers.array_length(arr) # You can use executor to print out the length of LoDTensorArray. input = fluid.layers.Print(arr_len, message="The length of LoDTensorArray:") main_program = fluid.default_main_program() exe = fluid.Executor(fluid.CPUPlace()) exe.run(main_program) # The printed result is: # 1569576542 The length of LoDTensorArray: The place is:CPUPlace # Tensor[array_length_0.tmp_0] # shape: [1,] # dtype: l # data: 11, # 1-D Tensor with shape , whose value is 11. It means that the length of LoDTensorArray # is 11. # dtype is the corresponding C++ data type, which may vary in different environments. # Eg: if the data type of tensor is int64, then the corresponding C++ data type is int64_t, # so the dtype value is typeid(int64_t).Name(), which is 'x' on MacOS, 'l' on Linux, # and '__int64' on Windows. They both represent 64-bit integer variables.