^j!dZddlZddlZddlmZddlmZddlmZddl Z ddl m cm Z ddl m Z ddlmZdd lmZdd lmZdd lmZdd lmZmZdd lmZmZddlmZddlm Z ddl!m"Z"m#Z#m$Z$m%Z%m&Z&m'Z'ddl(m)Z)ddl*m+Z+ddl,m-Z-m.Z.m/Z/e&j`e1Z2dZ3dZ4dZ5de jlde jlfdZ7e$deGdde"Z8e$deGd d!e"Z9e$eGd"d#e"Z:Gd$d%e jvZ<Gd&d'e jvZ=Gd(d)e jvZ>Gd*d+e jvZ?Gd,d-e jvZ@Gd.d/e jvZAGd0d1e jvZBGd2d3e jvZCGd4d5e jvZDGd6d7eZEGd8d9e jvZFGd:d;e jvZGGd<d=e jvZHGd>d?e jvZI dfd@e jvdAe jldBe jldCe jldDe jldzdEeJdFeJfdGZKGdHdIe jvZLGdJdKe jvZMGdLdMe jvZNGdNdOe jvZOGdPdQe jvZPGdRdSeZQGdTdUe jvZRGdVdWe jvZSe$GdXdYeZTGdZd[eTZUe$d\Gd]d^eTZVe$Gd_d`eTZWe$GdadbeTZXe$GdcddeTZYgdeZZy)gzPyTorch CLAP model.N)Callable) dataclass)Any)nn)initialization)ACT2FN)create_bidirectional_mask)GradientCheckpointingLayer)BaseModelOutputBaseModelOutputWithPooling)ALL_ATTENTION_FUNCTIONSPreTrainedModel)Unpack)apply_chunking_to_forward) ModelOutputTransformersKwargsauto_docstringcan_return_tuplelogging torch_int)merge_with_config_defaults)capture_outputs)ClapAudioConfig ClapConfigClapTextConfigc|j\}}}|dddddddfjdd|d}|j|||z|}|S)ae Interpolate data in time domain. This is used to compensate the resolution reduction in downsampling of a CNN. Args: hidden_states (`torch.FloatTensor` of shape (batch_size, time_length, classes_num)): Input hidden states ratio (`int`): The ratio of the length of the output to the length of the input. Nr)shaperepeatreshape) hidden_statesratio batch_size time_length classes_num upsampleds q/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/clap/modeling_clap.py interpolater)/sX.;-@-@*ZkaD!m,33Aq%CI!!*kE.A;OI c|j\}}}}|j|||z|||z||}|jddddddjjd|||}|S)aR Returns the resized hidden states. The output shape should be `(batch_size * num_windows, window_size, window_size, num_channels)` Args: hidden_states (`torch.FloatTensor` of shape `(batch_size, height, width, num_channels)`): Input hidden states window_size (`int`): Window size rrrrviewpermute contiguous)r" window_sizer$heightwidth num_channelswindowss r(window_partitionr9@s}/<.A.A+J|!&&Fk);8Lk[gM##Aq!Q15@@BGGKYdfrsG Nr*c|jd}|jd||z||z|||}|jddddddjjd|||}|S)a Merges windows to produce higher resolution features. Args: windows (`torch.FloatTensor` of shape `(num_windows * batch_size, window_size, window_size, num_channels)`): Input windows window_size (`int`): Window size height (`int`): Height of the resized audio width (`int`): Width of the resized audio r/rrrr,r-r.r0)r8r4r5r6r7s r(window_reverser;Usn==$Lll2v4e{6JKYdfrsGooaAq!Q/::<AA"feUabG Nr*logitsreturnctjt||j}tj j ||S)Ndevice)torcharangelenr@r functional cross_entropy)r<labelss r(contrastive_lossrGjs1 \\#f+fmm