bi ddlZddlmZddlmZ ddejdede de de de de d ejfd Z Gd d ejZ Gd dejZy)N timesteps embedding_dim freq_shift min_timescale max_timescaleflip_sin_to_cosscalereturnc|jdk(sJd|dzdk(s Jd|dt|dz}tj||z ||z z }|t j t j |tj| zz} t j|dt j| dz} || z} |r@t jt j| t j| gd} n?t jt j| t j| gd} t j| t j|d|g} | S) aReturns the positional encoding (same as Tensor2Tensor). Args: timesteps (`jnp.ndarray` of shape `(N,)`): A 1-D array of N indices, one per batch element. These may be fractional. embedding_dim (`int`): The number of output channels. freq_shift (`float`, *optional*, defaults to `1`): Shift applied to the frequency scaling of the embeddings. min_timescale (`float`, *optional*, defaults to `1`): The smallest time unit used in the sinusoidal calculation (should probably be 0.0). max_timescale (`float`, *optional*, defaults to `1.0e4`): The largest time unit used in the sinusoidal calculation. flip_sin_to_cos (`bool`, *optional*, defaults to `False`): Whether to flip the order of sinusoidal components to cosine first. scale (`float`, *optional*, defaults to `1.0`): A scaling factor applied to the positional embeddings. Returns: a Tensor of timing signals [N, num_channels] zTimesteps should be a 1d-arrayrzEmbedding dimension z should be even)dtype)axis)ndimfloatmathlogjnpexparangefloat32 expand_dims concatenatecossinreshapeshape) rrrrrrr num_timescaleslog_timescale_incrementinv_timescalesemb scaled_timesignals [/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/diffusers/models/embeddings_flax.pyget_sinusoidal_embeddingsr%s=< >>Q @ @@  1  !X%9-#XX !=A-.N"hh}}'DEZdIde"SWWSZZckk-Z^u]u-u%vvN //)Q '#//.!*L LC#+K#''+"6 8L!MTUV#''+"6 8L!MTUV [[#))I"6q"9=!I JF MczeZdZUdZdZeed<ejZ ejed<e jdZ y)FlaxTimestepEmbeddinga= Time step Embedding Module. Learns embeddings for input time steps. Args: time_embed_dim (`int`, *optional*, defaults to `32`): Time step embedding dimension. dtype (`jnp.dtype`, *optional*, defaults to `jnp.float32`): The data type for the embedding parameters. time_embed_dimrctj|j|jd|}tj|}tj|j|jd|}|S)Nlinear_1)rnamelinear_2)nnDenser*rsilu)selftembs r$__call__zFlaxTimestepEmbedding.__call__Rs\Orxx++4::JOPTUwwt}Orxx++4::JOPTU r&N) __name__ __module__ __qualname____doc__r*int__annotations__rrrr/compactr4r&r$r(r(Ds;NC{{E399"ZZr&r(c`eZdZUdZdZeed<dZeed<dZ e ed<e jdZ y ) FlaxTimestepsa Wrapper Module for sinusoidal Time step Embeddings as described in https://huggingface.co/papers/2006.11239 Args: dim (`int`, *optional*, defaults to `32`): Time step embedding dimension. flip_sin_to_cos (`bool`, *optional*, defaults to `False`): Whether to flip the sinusoidal function from sine to cosine. freq_shift (`float`, *optional*, defaults to `1`): Frequency shift applied to the sinusoidal embeddings. r)dimFrr rc\t||j|j|jS)N)rrr)r%r?rr)r2rs r$r4zFlaxTimesteps.__call__ks)( TXXt?S?S`d`o`o  r&N)r5r6r7r8r?r9r:rboolrrr/r;r4r<r&r$r>r>Zs< CM!OT!JZZ  r&r>)r r g@Fg?)r flax.linenlinenr/ jax.numpynumpyrndarrayr9rrAr%Moduler(r>r<r&r$rHs   !-{{--- -  -  - - [[-`BII, BII r&